SYSTEM TO NAVIGATE AN OFF-ROAD TRUCK AND METHOD FOR NAVIGATION FROM A FIRST HEAVY EQUIPMENT TO A TAR

专利摘要:
system and method for guided maneuvering of a mining vehicle to a target destination A system and method for navigating a first heavy equipment to a target destination is provided. the location of the target destination is obtained from a database of distributed objects. the location of the target destination is at least partially determined by the position of a second heavy equipment. a position sensor identifies the current position and orientation of the first heavy equipment, and a path from the current position of the first heavy equipment to the location of the target destination is calculated. the calculated route is selected to avoid hazards. the progress of the first equipment weighed along the calculated route is monitored using the position sensor. when the first heavy equipment deviates from the calculated route, a message is sent to an operator of at least one of the first heavy equipment and one of the second heavy equipment.
公开号:BR112014002503B1
申请号:R112014002503-7
申请日:2012-08-23
公开日:2021-06-01
发明作者:Michael W. Lewis；Andree Rottig；Lucas Van Latum
申请人:Modular Mining Systems, Inc；
IPC主号:

专利说明:

FIELD OF THE INVENTION
This disclosure is related to systems and methods for providing automated guidance directions to heavy equipment operators and, specifically, to a system and method for providing assistance in maneuvering with guidance to heavy equipment operators in proximity to other heavy equipment, hazards, or geographic aspects. BACKGROUND OF THE INVENTION
Mining environments, particularly open-pit surface mining environments, present unique challenges to maintaining the safe operation of vehicles. The flagship of a modern surface mine is an off-road mine truck, which is a dump truck capable of carrying up to four hundred, and in some cases more than four hundred tons of material. Off-highway trucks are some of the largest land vehicles ever built. As such, they are characterized by limited maneuverability, relatively slow acceleration and deceleration, and poor sight lines on either side of the vehicle. In particular, the rear and opposite side to the operator's cabin of an off-road mine truck present huge blind spots for the off-road truck operator.
Within a mining environment there can be many other vehicles, such as wheel loaders, tractors, bucket reclaimers or other equipment that are similarly difficult to control. Because vehicles are very large, they can have large blind spots, large turning radius and slow braking capabilities, making navigating vehicles to a given destination extremely difficult. In many cases, however, by precisely positioning these vehicles in close proximity to other vehicles or geographic aspects of the mine, the mine's efficiency can be vastly improved. Furthermore, through precise navigation, the risk of injury or material damage resulting from a collision can be mitigated.
In an example of conventional open-pit mining operations, material is blasted from one, picked up by a wheel loader, and loaded onto the body of an off-highway truck. The off-road truck then moves the material to a crusher for processing. Loaders can be several times larger than an off-highway truck. A typical electric wheel loader can measure 100 feet (30 meters) in length from the rear of the tracker portion to the end of the bucket. The total height of the wheel loader can measure 70 feet (21 meters) with a typical bucket height of 45 feet (14 meters). 80 feet (24 meters) is a typical distance from the center of rotation of a wheel loader to the distal end of the bucket.
Off-road truck loading tends to be a bottleneck in the operation in the process of extracting material from a mine. For convenience, an off-road truck will return along a path that is perpendicular to one face of the excavation relative to a position on one side of the wheel loader. Once the truck is in position beside the wheel loader, the wheel loader operator will take material from the face of the excavation and load the truck. Once loaded, the truck proceeds to a crusher. Given the size and responsiveness of a conventional mine truck, the process of navigating a truck to a target position can take some time. In addition, a collision between an off-road mine truck and a wheel loader or other mining equipment can be catastrophic, resulting in not only injury or death, but millions of dollars in equipment damage and downtime. Thus, off-road mine truck drivers tend to be hesitant when moving their vehicles into position for loading, further reducing vehicle efficiency.
Ideally, as a first truck is being loaded on one side of a wheel loader, a second truck will move into position on the other side. This maximizes the use of the wheel loader, allowing it to be continuously involved in the loading operation, rather than waiting for the next truck to move into position.
Fig. 1 shows a conventional solution for assisting an off-road mine truck to navigate a loading area, in addition to a wheel loader. In the arrangement of Fig. 1, the electric wheel loader 105 is working on the face of a mine excavation. Electric wheel loader 105 includes bottom mount 110. Bottom mount 110 includes first and second treads 115a and 115b. The electric wheel loader 105 includes a top mount 120, which is rotatably coupled to the bottom mount 110 by means of a rotatable bearing 125. The top mount 120 includes boom 127. Attached to boom 127, on a hinge is an arm 130. The distal end of arm 130 is a bucket 135. Top assembly 120 also includes a cab 140, in which an electric wheel loader operator 105 is located. In the operation of the example shown in Fig. 1, the electric wheel loader 105 is electrically energized. through a 145 tether dragline that provides electrical power to 105 shovel. Other wheel loaders, such as hydraulic wheel loaders, may not be powered through a tether dragline or power cable, but may operate independently instead. In both cases the top mount of a wheel loader often features a large frame that extends rearward, away from the wheel loader cab. As the wheel loader rotates, both the boom and the rear of the top mount can pose a hazard to nearby objects as it rotates around the wheel loader rotating bearing. Because the wheel loader and top mount surround additional machines for power generation, the top mount of a hydraulic excavator, which does not rely on a dragline for power, generally extends further in a direction to the rear of the cab. of the wheel loader.
The conventional arrangement of Fig. 1 shows a first off-road mine truck 150 in condition to receive material from the wheel loader 105. However, during loading of the first off-road truck 150, the wheel loader 105 rotates. back and forth between the first loading position and the face of the excavation 102. Similarly, the second off-road truck 165, which would be positioned on the opposite side of the wheel loader 105 relative to the first off-road truck 150 , must keep clear of the arch of the rear and corners of the top mount 120 while charging is taking place in the first charging position. The inherent risks of positioning an off-road truck behind an operating wheel loader often cause truck operators to delay movement into position until the wheel loader bucket is positioned in the second loading position. This results in wasted time and downtime.
The conventional solution to this problem is to attach a spear 155 ending in a highly visible marker 160 to the rear of the shovel 105. Occasionally, power line markers or traffic cones are used for the highly visible marker 160. For convenience, the operator of the second truck 165 will use the highly visible marker 160 to line up the second truck 165 while the first truck is being loaded. After the loading of the first truck 150 is complete, and the wheel loader rotates the bucket back to the face of the excavation 102 to pick up more material, the second truck 165 returns to position.
Systems have been developed that track the location of off-road mine trucks against potential hazards. For example, Co-owned Patent Application Publication No. US2009/0062971 discloses a GPS-based system for defining the routes and potential hazards of a mining environment. Patent No. US6,799,100 on co-ownership describes a permit system to control the interaction between autonomous vehicles in a mining environment, Patent No. 6,487,500 B2 to Lemelson et al., describes a system that uses GPS systems in vehicles, added with more accurate position sensors, to alert a vehicle operator of dangers in the operator's vicinity, including other vehicles. Patent No. 7,047,114 B1 to Rogers et al., describes a hazard warning system for marine vessels. The Rogers system takes GPS data and position information from marine vessels and forwards that hazard alert information to vessels based on the positions of other vessels, as well as fixed and semi-fixed hazards derived from nautical charts. SUMMARY OF THE INVENTION
Embodiments of the invention provide for the use of GPS and other geolocation technologies to guide off-road mine truck operators to position at a mining facility. Embodiments of the invention utilize position tracking and guidance systems to assist an operator of a mining vehicle, or to directly control an autonomous vehicle in positioning a vehicle at a predetermined location relative to another mining vehicle or a particular geographic feature.
In one implementation, the present invention is a system for navigating an off-highway truck through a mining environment to a target destination associated with a wheel loader. The target destination is located within a loading area near the wheel loader. The system includes a distributed object database storing information describing hazards, boundaries and target destinations within the mining environment, and a position sensor configured to identify an off-road truck's position and orientation. The position sensor is mounted on the off-road truck. The system includes a navigation apparatus configured to obtain a location of the target destination associated with the wheel loader from the distributed object database, wherein the location of the target destination is at least partially determined by the position of the wheel loader and by less, by the radius of the rear of the wheel loader dredge, radius of the corners of the wheel loader dredge, and the radius of the wheel loader boom. The navigation device is configured to calculate a route from the current position of the off-road truck to the location of the target destination. The calculated route is selected to avoid hazards in the mining environment. The navigation device is configured to use the position sensor to monitor the off-road truck's progress along the calculated route. The system includes a user interface configured to display at least a portion of the calculated route to an off-road truck operator.
In another embodiment, the present invention includes a method for navigating a first heavy equipment to a target destination. The method includes obtaining a location of the target destination from a database of distributed objects. The location of the target destination is at least partially determined by the position of a second heavy equipment. The method includes using a position sensor to identify the current position and orientation of the first heavy equipment, and calculating a route from the current position of the first heavy equipment to the location of the target destination. The calculated route is selected to avoid hazards. The method includes monitoring a progress of the first weighed equipment along the calculated route using the position sensor and, when the first weighed equipment deviates from the calculated route, issuing a message to an operator of at least one of the first and second equipment heavy.
In another embodiment, the present invention includes a method for navigating an off-highway truck to a loading area. The method includes providing a location of the heavy equipment, and, based on the location of the heavy equipment, defining at least a first and a second load envelope in a database of distributed objects. The method includes navigating the off-highway truck in one of the first and second loading envelopes.
Embodiments of the invention have a number of advantages. Embodiments of the invention utilize existing route definition and navigation systems to guide off-road mining truck operators to position with more speed and confidence than are provided by prior ad-hoc spotting techniques. This allows for maximum utilization of wheel loader power time, allowing continuous loading under systems in accordance with the invention. In various embodiments according to the invention, electric wheel loaders do not need to reposition themselves or wait for an off-road truck to arrive in position. In addition, off-road trucks can be guided along routes that are free from hazards.
Other advantages and features of the invention will become apparent to those skilled in the art after reading the detailed description and claims below. BRIEF DESCRIPTION OF THE FIGURES
Fig. 1 is a diagram illustrating a conventional arrangement for guiding off-highway trucks to a loading position.
Fig. 2 is a schematic diagram of an open-pit mining environment with a network data holding and transmission system in accordance with an embodiment of the invention.
Fig. 3 is a functional block diagram showing the components of a navigation system operating on a mobile computing device located in a vehicle in accordance with an embodiment of the invention.
Fig. 4 is a diagram showing an example arrangement of an off-road mining truck and a wheel loader, where loading areas are arranged close to the wheel loader.
Fig. 5 is a flowchart illustrating an example method for navigating a vehicle to a target destination in accordance with an embodiment of the invention.
Fig. 6 is a flowchart illustrating the steps of an alternative method for navigating a mining vehicle to a destination in accordance with the present disclosure.
Figs. 7-12 are flowcharts illustrating additional details of several of the steps of the present method.
Fig. 13 shows an example of using the present system to help trucks enter and exit defined loading areas close to the wheel loader. DETAILED DESCRIPTION OF THE INVENTION
Some of the functional units described in this specification have been named as modules in order to more particularly emphasize their implementation independence. For example, a module can be implemented as a hardware circuit comprising custom VLSI circuits or gate arrays, ready-to-use semiconductors such as logic chips, transistors or other discrete components. A module may also be implemented in programmable hardware devices, such as field programmable gate arrays, programmable logic arrays, programmable logic devices, or the like.
Modules can also be implemented in software for execution by various types of processors. An executable code identification module can, for example, comprise one or more logical blocks of physical or computer instructions that can be, for example, organized as an object, procedure or function. However, the executables of an identified module do not need to be physically located together, but can comprise different instructions stored in different locations, which when put together logically comprise the module and achieve the stated objective for the module.
In fact, an executable code module can be a single instruction, or many instructions, and it can even be distributed over several different code segments, among different programs, and across different memory devices. Similarly, operational data can be identified and illustrated here within modules, and can be incorporated in any suitable form and organized within any suitable type of data structure. Operational data can be collected as a single dataset, or it can be distributed over different locations, including over different storage devices, and it can exist, at least partially, as merely electronic signals in a system or network.
Reference to a signal carrying medium may take any form capable of generating a signal by causing a signal to be generated or by executing a machine readable instruction program with a digital processing apparatus. A signal-carrying medium can be incorporated by a transmission line, a compact disk, a digital video disk, a magnetic tape, a Bernoulli drive, a magnetic disk, punch cards, flash memory, integrated circuits, or other memory device for digital processing apparatus.
Included schematic diagram flowcharts are generally established as logic diagram flowcharts. As such, the described order and named steps are indicative of a modality of the presented method. Other steps and methods that are equivalent in function, logic, or effect with respect to one or more steps, or portions thereof, of the illustrated method can be devised. Furthermore, the format and symbols employed are provided to explain the logical steps of the method and are understood not to limit the scope of the method. Although various matrix types and line types can be employed in diagram flowcharts, they are intended not to limit the scope of the corresponding method. In fact, some arrays or other connectors can only be used to indicate the logical flow of the method. For example, an array may indicate an indefinite waiting or monitoring period between enumerated steps of the described method. Furthermore, the order in which a particular method occurs may or may not strictly be faithful to the order of the corresponding steps shown.
Furthermore, the described aspects, structures or features of the invention may be combined in any suitable way with one or more embodiments. In the following description, numerous specific details are provided, such as programming examples, software modules, user selections, network transactions, database queries, database structures, hardware modules, hardware circuits, chips hardware, etc., to provide a full understanding of the embodiments of the invention. However, one skilled in the relevant art will recognize that the invention can be practiced without one or more of the specific details, or with other methods, components, materials, and so on. In other cases, well-known structures, materials or operations are not shown or described in detail to avoid obscuring the particulars of the invention.
This invention is described in preferred embodiments in the description below with reference to the Figures, in which like numbers represent the same or similar elements. Reference throughout this specification as "mode", "an embodiment" or similar language means that a particular aspect, structure, or feature described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the expressions "in modality", "in a modality" and similar expressions throughout this specification may, but not necessarily, all refer to the same modality.
Where "data storage media" or "computer readable media" is used, Applicants denote an information storage medium in combination with the hardware, firmware and/or software necessary to record information and read the information contained therein, in the information storage medium. In certain embodiments, the information storage medium comprises a magnetic information storage medium, such as, but not limited to: a magnetic disk; magnetic tapes; and the like. In certain embodiments, the information storage medium comprises an optical information storage medium, such as, but not limited to: a CD; DVD (Digital Versatile Disc); HD-DVD {High Definition DVD); BD (Blue-Ray Disc)', and the like. In certain embodiments, the information storage medium comprises an electronic information storage medium, such as, but not limited to: a PROM; EPROM; EEPROM; Flash PROM; CompactFlash, smartmedia; and the like. In certain embodiments, the information storage medium comprises a holographic information storage medium.
Reference to the term "signs" is made throughout this specification. Signals can be any time-varying electromagnetic waveform, encoded or not encoded with recoverable information. Signals, within the scope of the present specification, may or may not be modulated according to any modulation or coding scheme. Furthermore, any Fourier component of a signal, or combination of Fourier components, must itself be considered a signal, as this term is used throughout this specification.
The present system facilitates the navigation of a mining vehicle or other heavy equipment such as an off-highway truck, wheel loader, tractor, or excavator to a desired target destination. The first system generates a list of target destinations. Target destinations can include static locations such as parking areas or repair facilities. In other cases, targets are mobile as they can be defined by changing geographic aspects or they can be defined by the position of another vehicle. A vehicle operator selects the intended target destination and the current one, the system calculates a more appropriate route to the intended destination. In other implementations, a supervisory controller selects the intended target. The supervisory controller can be implemented through an automated decision-making software system or an individual acting in a supervisory capacity. The route is selected to improve the vehicle's navigation efficiency to the target destination, but it can also be improved for safety. In other implementations, the path can also be optimized for various defined factors, on a “case-by-case” basis. Other factors, for example, could include operator experience, operator training requirements, or other operator or vehicle characteristics. After determining the route, the present system generates a display or other broadcast that demonstrates the route to the vehicle operator. As the vehicle navigates along the route, the present system provides constant feedback to ensure the operator is following the selected route.
Fig. 2 is an illustration of an open-pit mining environment in which systems and processes according to an embodiment of the invention are implemented. In the environment of Fig. 2, a plurality of mine off-highway trucks 205a-c operate on a route network for off-road mine trucks 210. Off-road mine trucks 205a-c perform loading tasks, for example, by moving a material between a wheel loader location 225, a crusher location 220 and a dump or storage location 215.
Each 205a-c mine off-highway truck is equipped with a navigation grid, communication and data compilation equipment that assists the off-road truck operator. Each off-road mine truck is equipped with a mobile computing device, for example, a personal tablet computer, a personal digital assistant, or a "smart phone" for implementing the present system. The mobile computing device includes the basic functionality common to all computing devices, specifically, data processing, storage, input and output devices such as monitors, speakers and either dedicated or on-screen keyboards, and communication interfaces network. The mobile computing device and its functionality is discussed in more detail below in relation to Fig. 3.
Each off-road mine truck mobile computing device is configured to receive data from a Global Positioning System receiver, which generates information about the truck's time-varying position. Additionally, or alternatively, each off-road mine truck's mobile computing unit receives data from a geolocation receiver, which generates information about the truck's time-varying position based on transmissions from ground-based transmitters. , within the mining environment. The mobile computing device can also communicate with onboard sensors such as gyroscopes or inertial navigation systems to locate the off-road truck within the mine environment.
Each off-road mine truck mobile computing device operates in communication with a transceiver, which exchanges data directly with other off-road mine trucks and with a 230a, 230b and 240 mine communications network. Fig. 2, the mine communications network is represented as a collection of wireless data transceivers, as suitable in implementing an 802.11g or 802.11n WiFi network, WiMax, GPRS, EDGE or equivalent. These network architecture examples, however, are not limited.
In practice, a mine communications network is typically an ad-hoc network made up of several wired and wireless portions. The distances over which communications can occur in a mining environment, coupled with the challenging and constantly changing topography of a mine, often preclude using wireless transceivers strictly. The wireless portions of a mine's communications network cannot always be implemented using contemporary standards, and may include slower older systems. The only requirement for a mine communications network is that it allow, at a minimum, data sharing between a central mine management computer located at a central location 235 with a plurality of off-road mine trucks 205a- ç. In certain embodiments, central location 235 includes a central communications node 240 and a central computing device, for example, the device discussed below with respect to Fig. 3. In certain embodiments, transceivers located on off-highway trucks of mine 205a-c can act as network peers and can share information with each other directly, without the need to be in direct communication with the broader mine communications network.
In the embodiment of Fig. 2, electric wheel loader 227 has a mobile computing device in communication with the communications network over a transceiver located on electric wheel loader 227. The mobile computing device, which performs functions similar to those performed by computing devices Mobile located on off-road mine trucks 205a-c is at least adapted to communicate the position of the 227 electric wheel loader to a central mine management application.
Fig. 3 is a diagram illustrating the functional components of the present system to aid in navigating a vehicle to a particular target destination.
The system includes a series of sensors, databases (both locally accessible and accessed through a wireless electronic communications network), and processing elements. The system is configured to generate a list of candidate target destinations for the vehicle. Target destinations may include fixed locations such as parking spaces, shredder locations, repair facilities, fuel refueling facilities, or dump sites. However, target destinations can also include moving targets, such as moving excavation faces within the mining environment, moving vehicles, or moving roads, for example. In some cases, target destinations are themselves defined by the positions of other objects. For example, a series of target destinations can be defined around the perimeter of a wheel loader, for example, on each side of the wheel loader, or it can be defined based on the position of other vehicles.
After generating the list of candidate target destinations, a user, supervisor, or supervising controller system selects a particular destination and, after verifying that the destination is valid, the system generates a route to the destination. The system can use the characteristics of the vehicle, driver (including, for example, the criteria to assess when the equipment has exceeded, or will exceed, its acceptable operating limits), and the known hazards and boundaries within the mining environment to calculate the route more apropriate. To select a specific route, a series of candidate routes can be generated. Courses are then ranked based on one or more criteria (eg safety, efficiency, or simplicity) and the best course is selected.
After selecting the best route for the selected target destination, the present system is configured to monitor a vehicle's movement along that route and provide constant feedback to a vehicle operator (either a human or a computer system, in the case of a autonomous vehicle). Constant feedback allows errors in the vehicle's path to be corrected. If, however, the vehicle navigates to a position where it is impossible or extremely difficult for the vehicle to return to the selected route (for example, it exceeds the vehicle's operational limits for the vehicle to do so), the present system can be configured to abort the current route and calculate a new one, replace the route to the selected destination.
One or more of the system components can be mounted inside the vehicle. However, in many implementations, one or more of the systems (eg the various databases) may be installed at a central location in the mine, where they can be updated and monitored by a central computer system. Generally, the system components shown in Fig. 3 can be installed directly on the heavy equipment vehicle and in direct communication with each other, or, if configured in a location away from the vehicle, the components are in wireless communication with the vehicle. and the components assembled therein. In other implementations, to provide redundancy, one or more of the systems illustrated in Fig. 3 can be duplicated either on the heavy equipment vehicle or at an offsite location, for example, to provide redundancy.
In Fig. 3 system 300 includes a position sensor 302. Position sensor 302 detects the position of the vehicle, for example, by triangulation of the vehicle's position relative to fixed satellites, as is known in the related GPS art. Position sensor 302 can also determine the vehicle's position by other means, such as by triangulation of the vehicle's position relative to terrestrial emitters located in a mining environment. In certain embodiments, Wi-Fi or WiMax network transceivers with known fixed positions can be used to provide terrestrial reference points. Position sensor 302 optionally can use a combination of methods or systems to determine position, for example, by determining an approximate position using GPS and performing error correction by ground references such as broadcast beacons mounted on around, or in the mining environment, or other terrestrial landmarks. In alternative embodiments, position sensor 302 also takes data from conventional RFID, RADAR, optical, or other collision or proximity warning systems. These conventional systems can provide a warning signal to the vehicle operator and/or equipment operator in the vicinity of the vehicle if a piece of equipment such as an off-road truck enters some predefined range of another piece of equipment . Position sensor 302 also includes one or more systems for determining vehicle orientation. In some cases, orientation can be determined by an electronic readout compass or other systems that use earth's magnetic poles to determine orientation. In other cases, vehicle orientation can be detected using one or more beacons or devices mounted in and around the land mining environment. In other cases, the vehicle orientation can be determined through algorithms, for example, by tracking a vehicle movement over time the sensor 302 can make an accurate determination of the vehicle orientation.
In other implementations, the 302 position sensor is assisted by a series of external devices that are mounted around various objects in the mining environment to aid in determining a vehicle's location and orientation. For example, a series of radars, LIDAR, lasers, or other object detection systems can be installed at the entrance to a crusher compartment or other equipment arranged around the mining environment. As a vehicle approaches the compartment, object detection systems can scan the compartment entrance and communicate the results of their scan to the vehicle. The vehicle uses information received from externally mounted object detection systems to supplement information obtained from position sensor 302 to generate a more accurate description of the vehicle's current position and orientation. These object detection systems can be used at any location in the mining environment, but can be particularly useful at compartment entrances or any location where the vehicle has to navigate particularly accurately. These externally mounted systems can be mounted to any equipment, aspects or objects within the mining environment (eg wheel loaders, buildings, crushers, etc.) Externally mounted systems allow for aggregation between vehicle and object pairs of positional data within of the mining environment, allowing for more accurate information that can be acquired from sensors mounted on a single vehicle. In an example of an externally mounted sensor system, a particular wheel loader might have a scanning laser mounted to accurately determine the position of a truck relative to the wheel. Data collected by the wheel loader using the laser system can then be communicated to the truck. This additional data can then be used by the truck to refine its own position data in relation to the wheel loader. The combination of positioning data collected by truck sensors as well as wheel loader sensors can then be used to navigate the truck in position next to the wheel loader, for example.
When interacting with externally mounted object detection systems, the external systems may only be able to observe a small portion of the vehicle. For example, when using LIDAR, or radar, for example, systems may only be able to communicate information concerning distance from the detection system to the side of the vehicle being presented to the object detection system - the other sides of the vehicle will be hidden. In this case, however, the present system can use the information received from the object detection system (including the location of the object detection system itself) to complement the data obtained from the position sensor 302.
System 300 includes a series of databases storing information useful in providing the functionality of the present disclosure. Distributed Object Database 304 stores a listing of objects that are present in the mining environment. Distributed object database 304 can store listings of candidate target targets (where each object in the database can be a target), the position of vehicles and the hazards or boundaries within the mining environment. Additional objects stored in the distributed object database 304 may include roads, parking areas, repair facilities, buildings or structures, dump areas, or power lines.
For each object, the distributed object database 304 may store, in addition to information about the location of each object, additional descriptive information identifying characteristics of the object. For example, in the case of vehicles, the database can store information describing the type of vehicle, its size and capacity, its current status (for example, loaded or unloaded, in use or not in use, etc.) , weight, and speed. For each vehicle, the database can also store information describing the vehicle operator (eg operator experience level, current assignment, working status, etc.) In case of hazards, the database can store information which describes the severity of the hazards and can define a series of hazard zones around each hazard. In fact, for each object, the database can define a series of danger zones around the object, with each zone (for example, a circular area defined around the danger) representing a different degree of risk. The database can also store information describing the roads and boundaries of the mining environment. In the case of roads, the database can store information describing a weight limit for vehicles crossing the road. Additional information such as incline, consistency and speed limit can be stored.
In some cases, the objects defined within the distributed object database 304 vary over time. As the mining environment is constantly modified by mining operations, almost every object within the 304 distributed object database can change over time. Thus, to ensure that the database 304 contains up-to-date information, the contents can be periodically updated through a connection to a central computer system that monitors the position and status of objects within the mine environment. Thus, whether distributed object database 304 is vehicle-based, a central computer system, or a combination of both, distributed object database 304 is configured to be constantly updated. Updates to the 304 distributed object database are efficiently distributed and the database reflects known objects within the mining environment at any point in time.
System 300 also includes vehicle condition monitor 306. Vehicle condition monitor 306 is configured to monitor one or more systems from within the vehicle and determine a current state or condition of those systems. In some cases, the 306 vehicle condition monitor communicates with one or more 308 vehicle sensors mounted around or on the vehicle to determine the current state of the systems. For example, the vehicle condition monitor 306 can monitor the vehicle's current fuel level status or fuel status, wheel positions (for example, in two-wheel or four-wheel configurations, the wheel angle can be measured), current selected gear (eg forward or reverse gears), braking status, etc. Vehicle Condition Monitor 306 can also determine if the vehicle is carrying a load or if the vehicle is empty. Vehicle Condition Monitor 306 can also track the vehicle's current speed. When the vehicle includes sensors for monitoring a “health” level of various vehicle components (eg engine temperature, tire pressure, battery charge levels), the 306 vehicle condition monitor can also communicate with the sensors to identify the current state of connected systems.
System 300 also includes configuration database 310. Configuration database 310 stores information describing certain vehicle attributes or conditions that must be met before the vehicle can perform a particular maneuver. For example, configuration database 310 may store a set of conditions that must be met before the vehicle can navigate to a particular target destination. Examples of conditions include that the vehicle is in forward gear, that all emergency interlock systems are disengaged, that the vehicle has enough fuel to complete a particular journey, that the vehicle is not scheduled for emergency maintenance than the vehicle must be submitted before navigation can take place, etc. The set of conditions included in the configuration database 310 may differ based on the vehicle and the specific maneuver the vehicle is trying to perform. Additional maneuvers may include dumping material, for which configuration database 310 could include a condition that the vehicle is carrying enough material to justify dumping. As another example, before attempting a refueling maneuver, configuration data 310 may specify a condition that requires the vehicle to have less than a certain amount of fuel reserves available.
Remote application 300 includes a number of modules that act on data received from one or more position sensors 302, distributed object database 304, vehicle condition monitor 306, and configuration database 310.
Remote application 300 includes navigation aid 322 that is configured to one or more of position sensors 302, distributed object database 304, vehicle condition monitor 306, and configuration database 310 to assist a vehicle operator. navigating to a particular target destination. To begin a navigation maneuver, the navigation aid 322 is configured to access the position sensor 302 and the distributed object database 304 to identify a listing of possible target destinations. The list of potential targets can be filtered by the navigation aid 322 of a series of variables. For example, the listing can be sorted based on vehicle proximity, with targets that are over a limited distance far away being filtered out. In addition, based on various vehicle attributes (attributes can be retrieved from vehicle condition monitor 306 and/or distributed object database 304), targets can be filtered. If, for example, the vehicle is a wheel loader, then targets that are only useful for off-road trucks can be filtered out. On the other hand, if the vehicle is an off-road truck, only useful targets for off-road trucks are used. Also, if off-highway truck is fully loaded, for example, only targets that are useful for fully loaded off-highway trucks are included in the list of potential targets.
After identifying the listing of potential targets, the navigation aid 322 can display the listing via screen 320. A user interface (for example, a touch screen, keyboard, voice input, or other system input system). user) allows a vehicle operator to select one of the targets. In other implementations, an automated system selects the target automatically and the selected target is displayed through the user interface.
After a determined target destination is selected, the navigation aid 322 uses the position sensor 302 distributed object database 304, vehicle condition monitor 306 and configuration database 310 to identify a best route for the vehicle to follow. , in order to maneuver in the target's position.
After identifying a best route, navigation aid 322 verifies that the vehicle can start moving using vehicle condition monitor 306 and configuration database 310. If so, navigation aid 322 constantly monitors the position the vehicle's current position in relation to the selected route using the position sensor 302. Using the vehicle's current position and orientation, the navigation aid 322 uses the screen 320 to provide feedback to the vehicle operator to assist the operator in maneuvering the vehicle while along the selected route. As the vehicle begins to deviate from the selected course, navigation aid 322, for example, can use screen 320 to provide feedback to the operator instructing the operator to turn the vehicle to return to the selected course. Alternatively, feedback could be provided through other user interfaces 324. For example, navigation instruction could be provided by vehicle rear view mirrors. A series of light sources (eg LEDs) can be arranged around the rear view mirror housing. By illuminating various combinations or colors of light sources, the vehicle operator can be instructed to hold the current course, drive left with a small degree, drive right with a small degree, drive left with a large degree , or drive right with a big degree. Light sources can also indicate when alignment with a defined route or course is not possible. In other implementations, user interface 324 may include a heads-up display or virtual reality output for displaying a particular route, route, or other information to the vehicle operator. In addition, voice instruction can help an operator navigate a specific route.
In one implementation, navigation aid 322 uses screen 320 to display a road map that illustrates the area in the vicinity of the vehicle. The map can be supplemented to display various objects that are described in the distributed object database 304. For example, screen 320 can describe the movements of other vehicles, the position of hazards, as well as danger zones defined around each. hazard, roads and various defined limitations within and around the mining environment. The road map representation can include any appropriate geographic aspects, such as acceptable routes, route attributes, hazards, areas outside the limitations and the location of points of interest, for example, individual work sites or pieces of equipment. Navigation aid 322 may optionally use screen 320 to display aerial imagery data generated, for example, by satellite or aerial photography that is sized and oriented to be co-extensive with the road map system representation and stored within the database. distributed object data 304, or other suitable data storage system.
The navigation aid 322 uses screen 320 to display the vehicle's location on the visual representation of the road map system, superimposed on aerial imagery data on screen 320. A graphical user interface (GUI), not shown, allows for a user to change the size and orientation of the road map system's visual representation and plot acceptable routes between the remote vehicle's current location and predefined points of interest.
In one implementation, navigation aid 322 is configured to operate in accordance with the methods illustrated in Fig. 5 or Fig. 6, for example.
System 300 may also include speed checker 312. Speed checker 312 is configured to check vehicle speed against an allowed speed obtained from distributed object database 304 for the vehicle's current position (determined by position sensor 302 ). 312 Speed Checker can calculate vehicle speed using
GPS or other data received from the position sensor or can read vehicle speed directly from the vehicle.
System 300 may also include proximity detector 314, which checks the vehicle's position as a function of the location of objects defined in the distributed object database 304. The vehicle's position is typically checked as a function of objects, such as, for example , defined hazards, other vehicles, areas that have been defined as out of bounds or not on a defined route, or areas that are on a defined route but which only authorize a specific direction of travel. In some cases, proximity detector 314 compares the vehicle's current position to a series of danger zones that are defined around a specific object. Depending on what (if any) danger zones the vehicle currently occupies, the 314 proximity detector can cause different alarm levels to be sounded to the vehicle operator.
Information from speed tracker 312, proximity detector 314, and one or more vehicle sensors 308 is passed to breach manager 316. Breach Manager 316 includes a set of rules that compares vehicle location and response with defined attributes in the distributed object database 304 and returns an indication if certain rules are violated. The rule set may comprise a route selected through a specific environment which has associated with it particular attributes which are inspected by the breach manager 316 in view of the received sensor data. For example, attributes might include operational tolerances of the vehicle attempting a particular maneuver. If tolerances are exceeded by the vehicle as it progresses along the route, 316 Violation Manager detects that a rule has been violated and issues the violation on an appropriate UI device such as a 320 screen or 318 speaker. violations 316 may command such conditions, optionally, if the remote vehicle violates a speed limit associated with a given route, if the vehicle advances in the wrong direction along a specific route, if the remote vehicle leaves a designated route, enters an area out of bounds, is approaching a hazard, or is too close to another vehicle. Rules included in breach manager 316 do not need to be Boolean. The breach manager can, for example, maintain various distances around hazards and trigger different indications as the vehicle approaches the hazard. Similarly, the tamper handle 316 may return different indications depending on how far off a designated road a vehicle is exposed.
Depending on the definition of the violation manager rule set 316, system 300 can take different actions when a rule is violated. When a rule is violated, the indication can be sent from the remote vehicle to a different location, eg a central application (not shown). When a vehicle comes too close to a predefined hazard, for example, a central office at the mine can be notified so that the event can be logged. The 316 tamper manager may additionally or alternatively provide an audible alarm on a speaker 318 or a visual alarm on a 320 screen visible to the driver of the remote vehicle.
System 300 may optionally include a function to alert the vehicle operator of messages, such as instant messages or electronic mail, relayed to system 300 from a central application not shown. When a user receives a message, audible alarms can be sent to speaker 318 and visual alarms as well as a display of the message itself can be sent to screen 320.
System 300 may also optionally include a data storage module that is updated from a central application (not shown). For example, system 300 may include a database or other data storage system that stores road map data, aerial image data, or data that varies over time on a remote vehicle position and/or condition. The database can be periodically updated by the central application (not shown) through a data synchronizer.
System 300, along with any necessary data storage and communications hardware can be included in a variety of popular devices, for example, handheld personal data assistants (PDAs), laptop computers or "smart" cell phones.
Fig. 4 shows an arrangement for navigation assistance according to an embodiment of the invention. The arrangement of Fig. 4 shows an electric wheel loader 405 positioned on one face of the excavation 402 for loading operations and describes an implementation of the present system, where an off-road truck uses the navigation system to aid in truck positioning. off-road in a loading position next to the wheel loader. In an implementation of the present system, the illustration shown in Fig. 4 is displayed by the navigation aid 322 on screen 320, as shown in Fig. 3.
There are a number of loader-related parameters of interest that are used to identify one or more target loading positions around the loader. The most important parameter is the wheel loader location, which can be measured directly by a GPS receiver or calculated based on the known dimensions of the wheel loader and the location of the GPS antenna. Additional useful parameters include dredge rear radius 420, dredge corner radius 415 and boom radius 425. These parameters define the outer envelope for the space the shovel will occupy during loading operations and can be set in a database, such as distributed object database 304, shown in Fig. 3. These parameters are illustrated in Fig. 4 with reference to the center of rotation of the wheel loader top assembly 405.
In Fig. 4, off-highway truck 404 wants to navigate to a position beside wheel loader 405 to receive material. Thus, the operator of the 404 truck uses the present system to initiate a navigation maneuver. First, the present system (eg, navigation aid 322 and screen 320 of Fig. 3) identifies two candidate target destinations, loading area 430 and loading area 435. The target destinations are displayed to the operator of the vehicle and the operator can select one of the destination destinations to start the maneuver. Alternatively, a target destination could be selected automatically, or a selection could be made by another individual or vehicle operator (eg a tractor operator on a dump, foreman, etc.) having control authority over the vehicle.
After selecting, for example, loading area 435 as the target destination, the present system determines an appropriate route 445 that truck 404 can take to reach loading area 435. As can be seen in Fig. 4, the boundary of path 445 is selected to avoid cable 407 and other hazards and boundaries that should be avoided by truck 404. Also, although boundaries 445 are relatively broad in the first place, as truck 404 approaches wheel loader 405, the path becomes narrow to ensure the truck 404 is safely guided to the loading area 435.
To aid truck 404 navigation in target area 435 the externally mounted object detection system 450 is mounted adjacent to area 435.
As the truck approaches area 435, the truck communicates with the 450 system to obtain additional information describing the 404 truck's position and orientation. In one implementation, the 450 system includes a LIDAR or radar object detection system.
As discussed below, various attributes of the loading area 435, such as size, preferred direction of entry, etc., can be at least partially determined by various characteristics of the 404 truck.
Fig. 5 is a flowchart illustrating method 500 for navigation assistance in accordance with an embodiment of the invention, which allows a truck to enter a defined loading area alongside a wheel loader. Method 500 is just an example method and represents a high level summary of steps taken by the present system, which are illustrated in more detail in Figs. 6-12.
In step 502 of method 500, a central application operating, for example, navigation aid 322 of Fig. 3 receives an identification of a wheel loader from which a truck wishes to receive material. Using the wheel loader identification, the system obtains information describing various attributes of the wheel loader (for example, dredge back radius, dredge corner radius, and boom radius) and, using these attributes, identifies a or more loading areas defined around the blade in step 504.
Candidate areas for loading are provided to the vehicle operator, and in step 506 the system identifies one of the loading areas that has been selected by the operator. In step 508, after the selected loading area is identified, the system identifies an appropriate loading path that can be traversed by the vehicle to enter the selected loading zone. As described below, the route is selected to avoid hazards and/or limitations that must be avoided by the vehicle as it navigates through the mining environment. Additional criteria can be defined to assess whether the chosen route has been successfully navigated.
In step 510, the defined loading path is displayed to the operator so that the operator can begin navigating the vehicle along the path. Also in step 510 the system continuously monitors vehicle characteristics (eg position, vehicle performance, and trajectory) to ensure that the vehicle stays within the defined path. As the vehicle starts to deviate from the displayed route, the present system
can provide feedback to the vehicle operator to help the operator return to the displayed route. In this way, the present system continuously monitors the vehicle's performance in relation to the defined route. In step 512, the vehicle reaches the identified loading position and the method ends.
Fig. 6 is a flowchart illustrating the steps of method 600 for navigating a mining vehicle or other heavy equipment to a destination in accordance with the present disclosure. For several of the steps shown in Fig. 6, additional flowcharts showing an example implementation of each step are shown in Figs. 7-12.
Method 600 can be implemented by system 300 illustrated in Fig. 3 and described above through other handheld computer systems in communication with various vehicle database and sensor systems that can also implement method 600. In implementations, for example, the method can be performed by computer hardware found in heavy equipment (eg, mining vehicles), by the centralized computer system, or it can be distributed across multiple systems. Method 600 uses data from multiple data sources to identify a suitable target and helps a driver or automated system navigate heavy equipment or other mining vehicle to that destination. Examples of data sources can be provided, for example, the navigation system, vehicle status system, configuration database, and distributed object database described above (eg, distributed object database 304, monitor of vehicle conditions 306, or configuration database 310). These databases can be made available by any appropriate computer system in communication with the software application execution method 600, such as software executed by the navigation aid 322 of Fig.3.
Method 600 starts by starting the guided activity in step 602. Step 602 may involve connecting to required databases or systems and powering up the sensors and computer systems needed to implement method 600. In step 604, the position and the current direction of the vehicle are determined. This step may also include determining the condition to start the vehicle and verifying that the vehicle is capable of initiating a special maneuver.
Fig. 7 is a flowchart, showing a series of steps 700 that can be taken to complete step 604 of Fig. 6. In step 702 the actual vehicle response, position, speed and direction are determined, for example, obtaining the corresponding data from the position sensor 302 and/or the vehicle condition monitor 306 of Fig. 3. Each data point associated with the current vehicle response, position, speed and direction can be associated with a level of confidence that indicates an anticipated accuracy of the data. Confidence levels can then be used to determine the margin of error that can be used to assess the safety of a particular maneuver.
At step 702, additional vehicle condition data is obtained from a vehicle condition monitor (e.g., via vehicle condition monitor 306 of Fig. 3). Vehicle condition data may include current gear selection, payload, handbrake status, or other information that identifies a vehicle condition that may be useful in determining a vehicle's ability to perform a particular maneuver. Additional information may include, for example, engine size, fuel reserves, tires or wheel types (indicating whether the vehicle is capable of handling certain types of terrain), maintenance or repair status (indicating, for example, whether the vehicle must avoid long-distance maneuvers). Vehicle condition data may also describe vehicle performance characteristics such as turn radius, maximum speed, optimum speed for fuel efficient operation, maximum slope the vehicle can climb, vehicle weight, or other information that is used to determine if the vehicle can proceed along a particular route in a mining environment.
Condition data can also include vehicle operator condition data. For example, if the vehicle operator approaches the end of his shift, a maximum distance or estimated time duration can be established for any specific maneuver to ensure that the driver can complete the maneuver in time to leave office hours.
Vehicle condition data can also include a current job assignment for the vehicle.
Given the vehicle position and current condition state in step 704, the system uses the position, vehicle conditions, and operator condition data to determine whether the vehicle is capable of initiating a particular maneuver or by identifying a class of proper maneuvers. The system does this by obtaining information from a configuration database (eg, 310 configuration database) that identifies the attributes of suitable maneuvers that can be performed by the vehicle and/or conditions that must be fulfilled before a vehicle can initiate a particular maneuver.
For example, if the vehicle is currently carrying a full (or nearly full) load, the vehicle will not be able to begin any maneuvers that involve the vehicle collecting additional material. As such, the authorized candidate maneuver set will only include maneuvers that involve the vehicle dumping at least a portion of that load. On the other hand, if the vehicle is empty, the set of maneuvers that involve dumping the material will be outside acceptable limitations.
In addition, if the vehicle is low on fuel, or requires immediate or urgent maintenance, the acceptable maneuver class may only include those that correct these deficiencies.
In addition, the driver's condition can be used to identify an acceptable maneuver class. If, for example, the driver is just a novice, certain more complex maneuvers may be unacceptable. Likewise, if the driver is reaching the end of the shift, the set of acceptable maneuvers may be limited based on that.
Conditions may require the vehicle to be stationary or moving at a particular speed or speed range before a maneuver can be initiated. Conditions may also require the parking brake to be engaged or disengaged before starting a maneuver.
At step 706, if vehicle position data (e.g., position, bearing, and speed), driver condition, and driver condition data are acceptable to initiate a maneuver, method 700 terminates. If, however, the data is outside acceptable ranges, the method moves to step 708, which allows an error to be displayed to an operator of the vehicle or other individuals or automated systems in communication with the current system.
Returning to Fig. 6, after collecting the vehicle position and condition data in step 604, the method determines an appropriate target position and direction in step 606. This step may involve the system obtaining a list of appropriate targets, with based on the data collected in step 604 and allows the vehicle operator to select one of these targets. Due to the fact that any particular mine environment can include a large number of targets, the listing generated by step 606 can be filtered based on the data obtained in step 604. For example, the target list will only include targets that are within from a certain distance and compatible with the current vehicle orientation as well as the current condition of the vehicle and driver.
Fig. 8 is a flowchart, showing a series of steps 800 that can be taken to complete step 606 of Fig. 6. In step 802, a listing of potential targets is obtained from the distributed object database ( for example, distributed object database 304 of Fig. 3). Because a mine can have many hundreds (or thousands) of potential targets, the list of candidate targets is filtered based on vehicle position and condition data, as well as operating condition data obtained in step 604 of Fig. 6. The listing can also be filtered based on vehicle target distance as well as vehicle current task assignment or vehicle capabilities.
As discussed above, target candidates may include static geographic aspects within the mine, such as compartments in a repair facility, compartments in a crusher, parking areas, or dump areas. In some cases, however, targets are mobile. For example, in a listing of targets that can be accessed by a wheel loader, targets might include dig faces in mining or other locations where the wheel loader can dig material. In this case, the target, despite moving slowly, is mobile.
In other cases, target locations may be determined by the location of a specific vehicle, which itself is mobile. For example, when an off-road truck needs to receive material from a wheel loader, there may be several candidate target destinations located around that wheel loader. For example, as shown in Fig. 4, most paddles will have at least two targets located on them, one on each side of the paddle. Other vehicles, such as larger wheel loaders, can provide more than two targets for an off-road truck.
By getting the list of candidate targets from the distributed object database, the distributed object database can filter the target list based on their availability. For example, if the distributed object database defines two targets about a wheel loader, but one of the targets is currently occupied by another off-road truck, the distributed object database will not return that target as a candidate target.
Similarly, if one or more compartments in a shredder are closed for repair, they would not be included in the candidate target list. Or, if some crusher compartments are preferred over others (for example, to balance wear on the crusher or to balance the flow of material through the crusher), particular compartments may be preferred over others with non-preferred compartments being filtered.
In some cases, where targets include a series of crusher compartments, targets may be filtered based on the material being carried by the vehicle. For example, when analyzing a vehicle position in which it picked up material from a wheel loader, the type of material being loaded by the vehicle can be characterized by determining the type of material being extracted at that location. Alternatively, the type of material being extracted by the off-highway truck can be indicated as part of that truck's assignment. The particular assignment can be obtained by the present system to identify potential eviction targets based on that assignment. Based on this characterization of truck loading, particular bins in a crusher can be filtered from the target list to ensure material is being delivered to the most appropriate crusher bin or compartments.
Information concerning whether a specific target is available, or otherwise busy, can be retrieved from the central computer system, for example, or can be updated in the distributed object database.
Having obtained the candidate target list from the distributed object database, the present system compares the candidate target list to vehicle position and condition data, as well as vehicle operator condition data. Based on this comparison, the listing of candidate targets is even more refined. For example, targets that are beyond a maximum distance, or are irrelevant based on the current vehicle assignment are filtered out. Similarly, targets that require a lot of skill for an untrained driver are filtered out if the driver doesn't have enough experience. Similarly, targets that require a lot of time to navigate are also filtered out if there is not enough time remaining in the driver's hours to reach that destination.
Candidate targets can also be filtered based on the vehicle's current condition. If the vehicle does not have current scheduled maintenance, targets relating to maintenance facilities can be filtered out. Additionally, targets can be filtered based on whether the vehicle is configured to carry more material, or needs to dump some material. In addition, if the vehicle is in need of fuel, targets that include fueling stations can be included in the candidate target list, where they would normally be filtered out.
At step 804, the system determines whether the vehicle is human controlled or automated. If controlled by a human, and the filtered listing of candidate targets generated in step 802 contains multiple entries, the listing is displayed to the operator in step 806 (eg, via screen 320 of Fig. 3). In one implementation, the listing is filtered by distance and how well the target matches the appropriate uses for the vehicle and its current assignment. An automated system or the vehicle operator can then select one of the targets at step 808. The vehicle operator can use an appropriate system user interface to make target selection.
In some cases, after performing step 808, the target selected by the operator is communicated to a mine supervisor for further authorization. For example, the selection can be communicated to the mine's central computer system, where the selection is displayed to a supervisor. The selection can be evaluated by the supervisor and the supervisor can approve or deny the selection. If approved, the method moves to step 810. However, if the supervisor denies approval, the method returns to step 806 and the operator can select another target.
In step 810, the target selected by the operator is displayed for confirmation by the operator. If the operator does not confirm the selection, then the system may generate an error, or it may return to step 806. However, if the operator confirms the selection, the method moves to step 812. In some implementations, to minimize the target selection time, steps requiring operator confirmation are ignored by the system. Furthermore, in some implementations the confirmation step illustrated by block 810 of Fig. 8 is removed from the system and, upon completion of step 808, the system proceeds directly to step 812.
Returning to step 804, if the vehicle is autonomously controlled, and multiple filtered targets are generated in step 802, the system moves to step 814. In step 814, a supervisor (e.g., an individual and/or system automated) reviews the list of targets generated in step 802 and selects the most appropriate target for the autonomous vehicle. The supervisor can be a human or in some cases an automated mine supervisory system. The automated system evaluates the target list in view of the other activities of other vehicles operating in the mine and automatically selects the most appropriate target. However, if only a single target was generated, the system selects that target and moves to step 812 (in some implementations, this single target also requires supervisor approval). In step 812, the position and direction of the selected target is determined and the target is displayed to the vehicle operator for confirmation. Then, the system can also check that all parameters associated with the selected target fit within predefined acceptable ranges.
Fig. 9 is a flowchart showing a series of steps 900 that can be taken to complete step 802 of Fig. 8. In step 902, information describing the selected target is obtained from the distributed object database, with based on the selected target. Target information can include whether the target is static or dynamic.
In step 904, the system assesses whether the target is static or dynamic (that is, able to move in a relatively short time frame). If static (e.g., a crusher compartment, fuel compartment, predetermined parking point, or predetermined dump point), at step 906, the system stores target position and associated data in a current target database. Associated data may describe a specific course the target must be approached on, the preferred orientation for the vehicle when positioned on the target, or other target-based considerations must be noted by the vehicle approaching or parking at the target.
However, if the target is dynamic, in step 908 the system evaluates the target to determine if the target position has been specified by an equipment operator (for example, by a loader operator specifying targets positioned on both sides of the shovel loader). In that case, if the target information has not changed (for example, the loader position has not changed and the operator has not indicated that the target is no longer valid), the system moves to step 906 and stores the target information.
However, if targets are set by the target equipment operator and have changed (or perhaps have changed), the system moves to step 910 where a request is issued to the target equipment operator to confirm, or re-establish the location of targets that are at least partially determined by the location of the target vehicle. In that case, new targets may have a lifetime associated with them, after which the targets are invalid.
Alternatively, targets can be associated with a set of conditions that determine whether the target is valid. For example, when a wheel loader operator defines a set of targets around the wheel loader (for example, targets 430 and 435 shown in Fig. 4), the targets can only be valid as long as the wheel remains stationary. However, if the wheel loader moves the location, the targets immediately become invalid and must be reset by the wheel loader operator. However, in some cases targets whose locations are defined by the target vehicle's target position can be located based on the current position and orientation of the target vehicle without confirmation or feedback from a vehicle operator.
After receiving the updated or confirmed target locations from the target equipment operator, the target information is stored in step 906. After storing the target information (for example, in navigation aid 322 of Fig. 3.), the Target information can be compared with the vehicle's current position and orientation to calculate a direction towards the target.
Returning to Fig. 8, after determining the target location and direction in step 812, as well as other target information (for example, other parameters that can be used to identify a suitable approach to the target, as determined in step 812, or any previous steps), the system checks that the target location and information are within acceptable parameters. For example, the system can verify that the target is within the vehicle range. In addition, all parameters such as target position, direction, and any other data related to target position and direction can be checked to ensure that they have not expired, are within acceptable limits, and have confidence levels that exceed predetermined limits . For example, if the last update of the position of a target vehicle or other moving object was recorded more than a given number of minutes or seconds in the past, then the position may no longer be valid. Of course, validity requirements and confidence levels can differ between positions or objects of fixed and moving targets, with fixed targets having a longer validity duration than moving targets.
Returning to Fig. 6, after determining the target position and direction in step 608, the system identifies hazardous conditions or boundaries that may exist between the vehicle and the selected target. To perform this step, the system can access the distributed object database that stores equipment positioning data, hazardous areas, geographic aspects and other objects or aspects within the mine environment. The distributed object database can also store additional information describing the hazards, such as a series of risk zones that can be defined around each hazard, or speed limits that can be set for particular routes through the mine.
Fig. 10 is a flowchart showing a series of steps 1000 that can be taken to complete step 608 of Fig. 6. At step 1002, the system obtains all hazardous conditions and boundaries existing within a predetermined distance from the vehicle and the selected target. Hazards and limitations can be taken from the distributed object database described above. Each dangerous situation can have an associated consequence for approaching the dangerous condition. For example, each hazard can be associated with potential consequences, such as "injury or death", "property damage", or "degradation of performance" in the event that the vehicle comes into contact with, or enters a risk zone of, a specific hazard. .
Each hazard or boundary obtained from the distributed object database may have associated with it (a) a specific accuracy index indicating a confidence range for accuracy of a particular hazard or boundary location.
In some cases, hazards can be quite dynamic. For example, hazards such as wiring, blast zones, other vehicles, or mining excavation faces or cliffs can move continuously throughout the day. Thus, the distributed object database is configured to store the most up-to-date location information for all hazards and boundaries that are accessible.
If the accuracy indices or confidence levels associated with the hazards and boundaries are within acceptable levels, the system moves to step 1004 to create a virtual map of the mine site between the vehicle and the selected target that maps the hazards and boundaries which must be avoided by the vehicle when navigating to the selected target. In some implementations, the map has a limited validity period. Upon expiration of the validity period, the map is rebuilt to ensure that the vehicle does not attempt to navigate using an old map.
Returning to Fig. 6 in step 610, after identifying the dangerous conditions or boundaries that may exist between the vehicle and the selected target, the system calculates a best route for the vehicle to the destination selected in step 610 by calculating a route from the current position of the vehicle to the position of the target. The course is selected based on the criteria defined for the success of the specific maneuver, as well as the established error conditions. Step 610 may also include calculated acceptable tolerances and/or safe movement lanes along the calculated best course.
Fig. 11 is a flowchart, showing a series of steps 1100 that can be taken to complete step 610 of Fig. 6. At step 1102, the system first identifies various vehicle performance characteristics. Features can include driving settings such as whether the vehicle has four-wheel drive steering and vehicle turning radius, performance information such as stopping capabilities, and vehicle characteristics such as weight (both loaded and unloaded). Depending on the vehicle type, vehicle characteristics may also include defined buffer zones around the vehicle, where the vehicle buffer zone cannot overlap with any other hazards or boundaries identified by the system. For example, buffer zones on larger vehicles can be particularly large to ensure that the vehicle does not get close enough to a specific hazard or boundary to create a risk that an accident could occur. In some implementations, buffer zones are defined by the maximum area that specific vehicle components can cover. For example, buffer zones around a wheel loader can include the entire area that can be accessed by the wheel loader (for example, the area covered by the bucket to the full extent when processed through 360 degrees). In other cases, the buffer zones can be expanded to allow the vehicle's turning wheel to protrude out of the vehicle's body during a turning maneuver. These vehicle characteristics (including the vehicle's buffer zone) can be obtained from a vehicle condition monitor and/or configuration database (eg, 306 vehicle condition monitor and/or database of configuration 310).
In step 1104, after obtaining the characteristics of the vehicle, the system generates a first potential path between the vehicle and the selected target. The first potential leg can be generated using semi-random optimization and route planning, or any other suitable process or algorithm to determine a candidate leg. The route can be optimized based on the data obtained in step 1102 as well as any additional information describing the intermediate terrain (for example, the virtual map generated in step 1004 of Fig. 10), or the selected target.
Potential routes may be limited by vehicle characteristics. For example, based on the vehicle's turning radius, paths can be generated that do not require the vehicle to turn with a radius that is narrower than the vehicle's own optimum turning radius. Likewise, based on the vehicle's ability to climb steep steps, the route can be generated to avoid any roads or other routes that require the vehicle to climb a ramp that is too steep. In addition, based on the vehicle's weight (both loaded and unloaded), the route can be selected to ensure that the vehicle will only travel on roads or routes that can support the required weight.
In one implementation, potential paths are generated to minimize the accumulation of ruts within the area between the vehicle and the target. As such, the system can be configured to inject a certain amount of 'tripidation' into a specific route to ensure that vehicles traveling on the same route do not create destructive or dangerous ruts. In one implementation, the position of each path through the mine environment can be adjusted based on changing road conditions. As more and more vehicles use a specific road For example, the position of the route set through the road can be adjusted to avoid too many vehicles driving in the same area. Thus, in specific congested areas, the system can generate "anti-grooving" paths, which are configured to prevent multiple vehicles from using the identical (or similar) paths to prevent ruts.
In one implementation, to prevent ridges, the paths generated through congested areas are periodically varied, within acceptable boundaries, to prevent ridge accumulation. Detour can be randomly selected from alternative trajectories that ensure a continuous and constant journey within the congested area containing the originally determined route.
After identifying a potential first course, the system assigns a score for the first potential course based on difficulty, efficiency, safety, and/or tolerance level for course deviations. In an implementation, difficulty is evaluated based on the number of laps that are required by a driver tasked with a particular task. Difficulty can also be affected by vehicle type. For example, on some off-road trucks the driver sits on the left side of the vehicle. In this case, because the driver has better visibility from the left side of the vehicle compared to the right, left-hand turns are rated easier than right-hand turns in the scoring algorithm. Similarly, when the selected target is in close proximity to another vehicle (eg, a target located next to a wheel loader), the difficulty can be assessed based on the vehicle's visibility to an operator of the target vehicle. For example, when approaching a wheel loader, paths that allow the vehicle to be in sight of the wheel loader operator for a longer period of time will be rated easier than paths that obscure the loader operator's view of the vehicle. . By allowing for greater visibility, the wheel loader operator can more easily help the vehicle reach the desired target location.
In one implementation, to assess potential route safety, the system analyzes how close to identified hazards and boundaries a specific route will cause the vehicle to operate. While this analysis can be performed solely on the basis of proximity to specific hazards (or danger zones defined around specific geographic aspects or hazards) and boundaries, other factors can be used in assessing the safety of a specific route. For example, using the consequences described above for specific hazards or boundaries, each path could be classified for any combination of safety, productivity, or cost of a tiered approach. The first level would imply inefficiencies. For example, a specific route may be rated lower if it requires the vehicle to pass through a particularly congested area of the mine, or take a longer route, for example. There may be little risk or damage or injury in this case, but the route would still result in a loss of resources as it would take longer for the vehicle to reach the desired destination, and could consume more fuel as a result.
On a second level, courses can be scored based on the probability of damage to the equipment. For example, if a particular route causes a vehicle to pass through an area of the mine where vehicle damage is likely to occur, perhaps due to road conditions, or other traffic, the route may be scored lower than other routes .
Finally, on a third level, courses can be scored based on the probability of injury to mine workers. If, for example, a specific course causes a vehicle to pass through an area of the mine where injury is likely to occur (for example, near a blast site, or near cliffs or other large drop-offs), the course may be scored lower than other courses. In some cases, if there is any risk of injury, the route is immediately invalidated and a new route must be prepared.
In the level system described above, the levels can be scaled so that the risks of inefficiency do not result in a score as low as the risks of equipment damage, injury or death. In some cases, if a specific path creates any risk of injury or death, that particular path is immediately assigned a score of 0 (or any other score indicating that under no circumstances will the path be used) and the process restarts at block 1104 by generation of a potential new path.
In step 1108, if the score of at least one potential path exceeds a certain threshold the path is selected in step 1110. However, if there are no paths that have a high enough score, the method returns to block 1104 and a new path is generated. This process repeats until a course having a high enough score is generated.
In some cases, the system will initially generate a set of candidate pathways. Each course will then be scored, for example, using the algorithm described above. Candidate courses can then be ranked, with the highest ranked course (assuming your score exceeds a particular threshold) being selected.
Returning to Fig. 6, after generating a suitable path to the target, in step 612 the system issues vehicle control orders and begins monitoring vehicle movement to provide feedback to a vehicle operator (if present). Fig. 12 is a flowchart, showing a series of steps 1200 that can be taken to complete step 612 of Fig. 6.
At step 1202, the system determines whether the first vehicle is operated by a human driver or whether the vehicle is autonomous. If the vehicle is autonomous, in step 1204 the selected route is communicated to the vehicle's control system. The autonomous vehicle control person can then use the route to navigate the vehicle to the selected target.
However, if the vehicle is controlled by a human driver, the system obtains the vehicle condition parameters, and calculates the vehicle trajectory in step 1204.
In step 1208, the system analyzes the current position of the vehicle and the selected route and determines a trajectory feedback that causes the vehicle to follow the route. If, for example, the vehicle has strayed off course, the system displays trajectory feedback to the operator that causes the vehicle to return to the course in an efficient and safe manner.
In step 1210, the system identifies any deviation that exists between the vehicle's current trajectory and the trajectory determined in step 1208. Using the vehicle's condition data (eg, turn radius, stopping distance, etc.), then the system determines if any detected deviation is so large that the vehicle will not be able to return to the selected route based on the vehicle's performance capabilities. For example, the vehicle's turn radius may be too large to return the vehicle to the selected route. In this case, the system can generate an error alert to the operator, that the vehicle cannot return to the selected route. The operator can then restart the route selection process to generate a new route, or the system can automatically generate a new route. In some cases, the operator may have to navigate the vehicle away from the selected target to provide enough space for a suitable new course to be identified.
When alerting the vehicle operator concerning deviations from the chosen route, the present system may utilize any appropriate user interface device to communicate such information. Heads up displays or other device display screens, alert sounds, voice signals, or other indicators may be used to provide feedback to the operator.
Returning to Fig. 6, after generating trajectory feedback, the system enters a control circuit that allows the system to continuously monitor the vehicle's position and trajectory and generate feedback information that allows the vehicle to continue the selected route. In step 614, the operator of the vehicle (whether human driven or autonomous) controls the vehicle for a predetermined period of time in step 614. After that period of time has elapsed, the system evaluates the current position and direction of the vehicle in step 616. When assessing the vehicle's current position, the system can use a position sensor (eg, position sensor 302 in Fig. 3.) to identify the vehicle's current position and orientation. However, in some cases where externally mounted object detection systems are positioned around the selected target as the vehicle approaches the target, the vehicle may initiate communication with the object detection systems to gather additional data describing the vehicle's current position and orientation. Data received from the vehicle mounted position sensor can then be combined with data received from the external system to generate more accurate position and guidance data. At this time, the system can also access the hazard and boundary database to ensure that no new hazards have been created, or that hazards have not moved into the vehicle's path.
In step 618, the system assesses whether the vehicle has reached the selected target destination. If not, in step 620 the system evaluates whether the vehicle's current path and direction are within acceptable tolerances. If so, the system returns to step 612, analyzes the vehicle's current selected position, direction, and course, and displays a new feedback trajectory to help the vehicle operator navigate along the course. Depending on the system's implementation, feedback information may instruct the vehicle operator to turn the vehicle's steering wheel by a specific amount to navigate back on course. The system can also advise the driver to apply the brakes to reduce the vehicle's speed, or take other maneuvers that are configured to return the vehicle to the route.
If the vehicle's current route and direction are not within acceptable tolerances, the system returns to step 610 and recalculates a new route to guide the vehicle to the selected route.
When the position of the vehicle as determined in step 616 is determined to match the position of the selected target, the vehicle is considered to have arrived at the target destination. In this way, step 618 is satisfied and the system moves to step 622 to complete the maneuver. In step 622, the maneuver is completed and the data collected during the maneuver can be stored for later analysis.
For example, during a specific maneuver, the system can periodically record the current position and direction of the vehicle, the current route and information describing the current hazards and limits. This information can then be packaged and stored with metadata identifying the vehicle operator, current time, vehicle condition data, target information (eg vehicle identification target) and logical position. The dataset can be stored on an offline system for review.
In some cases, because the vehicle cannot navigate directly to a target destination, a series of inverse points can be defined in close proximity to the target destinations. Reverse points can be selected to allow a vehicle operator, for example, to perform a controlled turn before retreating to a specific target destination. Reverse points can be particularly useful, for example, when an off-road truck wants to navigate into position alongside a wheel loader to receive material.
Fig. 13 shows an example of using the present system to assist trucks in and out of defined loading areas near shovel 1305. The arrangement of Fig. 13 shows an electric excavator shovel 1305 positioned on a face of excavation 1302 for operations of shipments. Because the shovel can swing back and forth, there are two possible target destinations 1330 and 1335 that would allow a truck to position itself alongside the wheel loader 1305 to receive material.
When identifying possible loading positions, there are a number of loader-related parameters of interest that are useful when designing a guided loading scheme. The most important parameter is the wheel loader location, which can be measured directly by a GPS receiver or calculated based on the known dimensions of the wheel loader and the location of the GPS antenna. The dredge rear radius 1320, the dredge corner radius 1315, and the boom length 1325 are additional useful parameters. These parameters fix the outer envelope in the space that the wheel loader will occupy during loading operations, and represent an outer area from which loading positions are to be located. These parameters are illustrated in Fig. 13 with reference to the center of rotation of the top assembly of wheel loader 1305.
According to methods of the invention, two loading envelopes 1330 and 1335 are defined. Loading envelopes define the space in which off-highway trucks can be placed before loading begins. By defining the loading positions on each side of the 1305 wheel loader, loading off-highway trucks can be more efficient, as the 1305 wheel loader is not required to wait to access a fresh off-road truck. -parked. Instead, the shovel
1305 wheel loader can rotate around the new off-highway truck located on the other side of the 1305 wheel loader. 1330 and 1335 loader envelopes are set to be outside the arc defined by the rear and/or corner of the wheel loader, but inside from the bucket's reach. The size and orientation of the 1330 and 1335 loading envelopes may vary depending on the make and model of off-highway truck, which determines the size and height of the truck body.
Charging paths 1340 and 1345 are also defined as described above. Loading paths 1340 and 1345 demarcate the acceptable space in which an off-highway truck can travel as it does as it retreats into the loading envelope. Loading paths 1340 and 1345 will generally be wider the farther the truck is from the loading envelope, requiring increasing accuracy as the truck approaches the loading envelope. In addition, loading paths 1340 and 1345 are defined in hazard-free areas or other prohibited areas, for example, the area occupied by a dragline rope 1307 or overhead electrical cables.
Systems according to the invention also define inverse points 1350 and 1355. Inverse points 1350 and 1355 are the regions in which an off-highway truck can navigate before starting its reverse movement along loading paths 1340 and 1345 to the 1330 and 1335 loading envelopes.
Loading envelopes from 1330 and 1335, loading paths 1340 and 1345 and inverse points 1350 and 1355 can be defined, for example, in a distributed object database or can be generated on-the-fly by a navigation system, such as system 300 described above in relation to Fig. 3. The locations of these various aspects (e.g., loading envelopes 1330 and 1335, loading paths 1340 and 1345, inverse points 1350 and 1355) are accessed by the system (e.g. , system 300 of Fig. 3).
After identifying the various aspects, a navigation aid (eg, navigation aid 322 of Fig. 3) accesses the resources and uses them to guide off-road trucks from the mine to position according to the methods described above (see , for example, Fig. 6-12). In addition, the central application can assign one of the two inverse points 1350 and 1355 to a given truck as part of an off-highway truck dispatch system. For example, when the central application is informed that a first truck is located in a first loading envelope 1330, a second truck is given a second reverse point 1355 as a waypoint to navigate through it. Reverse points 1350 and 1355 are generally assigned to trucks in the direction of wheel loader 1305 in an alternating sequential fashion depending on the estimated time of arrival.
While one or more embodiments of the present invention have been illustrated in detail, one skilled in the art will understand that modifications and adaptations to these embodiments can be made without departing from the scope of the present invention as set forth in the claims below.

权利要求:
Claims (7)
[0001]
1. System (300) for navigating an off-road truck (404) through a mining environment to a target destination associated with a wheel loader, the target destination being located within a loading area close to the wheel loader, the system (300) characterized by the fact that it comprises: a distributed object database (304), the distributed object database (304) storing information describing the hazards, boundaries and targets within the mining environment a position sensor (302), the position sensor (302) configured to identify a position and an orientation of the off-road truck, the position sensor (302) being mounted on the off-road truck; navigation aid (322) configured to: obtain a target destination location (504) associated with the loader from the distributed object database, where the target destination location is at least partially determined by a position of the shovel here wheel loader, and at least one of a radius of the rear of the wheel loader dredge, a radius of the corner of the wheel loader dredger, and a radius of the wheel loader boom, calculate a path (445) from a current position of the truck outside - from road (404) to target destination location, calculated route (445) being selected to avoid hazards within mining environment, use position sensor (302) to monitor an off-road truck progress (404) along the calculated path (445), identify an off-road truck performance characteristic (1206), wherein the performance characteristic includes at least one off-road truck turn radius, a indication of whether the off-road truck (404) has four-wheel steer, and an off-road truck stopping capability, and if the off-road truck (404) deviates from the calculated route (445), use the performance characteristic to determine if the off-road truck (404) is able to return to the calculated route (445); and a user interface (324) configured to display at least a portion of the calculated route (445) to an operator of the off-road truck (404).
[0002]
A system (300) according to claim 1, characterized in that the navigation aid (322) is configured to, when the navigation aid (322) detects the vehicle deviating from the calculated route (445), to display an alert to an off-highway truck operator (404) using the user interface (324).
[0003]
3. System (300) according to claim 1, characterized in that the navigation aid (322) is configured to: obtain a plurality of target destinations (802) from the distributed object database (304) ;filter the plurality of target destinations (806) based on an attribute of the off-road truck (404); and display the filtered targets (808) using the user interface (324).
[0004]
4. System (300) according to claim 3, characterized in that the attribute includes at least one of a current off-road truck assignment (404), a fuel state of the off-road truck (404), and an off-road truck maintenance status (404).
[0005]
5. Method for navigating a first heavy equipment (404) to a target destination (430, 435), characterized in that the method comprises: obtaining a location of the target destination (430, 435) from a bank distributed object data (304) wherein the location of the target destination (430, 435) is at least partially determined by a position of a second heavy equipment (405); using a position sensor (302) to identify a current position and orientation of the first heavy equipment; calculating a route (445) from the current position of the first heavy equipment (404) to the location of the target destination (430, 435), the calculated route (445) being selected to avoid dangers; monitoring a progress (1208) of the first equipment weighed along the calculated path (445) using the position sensor; and when the first heavy equipment deviates from the calculated path (445): identification of a performance characteristic of the first heavy equipment (1206), wherein the performance characteristic includes at least one turning radius of the first heavy equipment, an indication of whether the first heavy rig has four-wheel steering, and the first heavy rig's stopping capability, using the performance characteristic to determine if the first heavy rig is capable of returning to the calculated route (445), and issuing a message to a at least one of the first heavy equipment and the second heavy equipment.
[0006]
6. Method according to claim 5, characterized in that it includes: obtaining a plurality of target destinations (802) from the distributed object database (304); filtering the plurality of target destinations (802) with based on an attribute of the first heavy equipment (404); and displaying filtered target destinations (808) using a user interface (324).
[0007]
7. Method according to claim 6, characterized in that the attribute includes at least one of a current assignment of the first heavy equipment (404), a fuel state of the first heavy equipment (404), and a maintenance state of the first heavy equipment (404).

类似技术:

---

公开号 | 公开日 | 专利标题

---

BR112014002503B1|2021-06-01|SYSTEM TO NAVIGATE AN OFF-ROAD TRUCK AND METHOD FOR NAVIGATION FROM A FIRST HEAVY EQUIPMENT TO A TARGET DESTINATION

---

US11143517B2|2021-10-12|Driver guidance for guided maneuvering

---

US9008886B2|2015-04-14|Method of modifying a worksite

---

WO2016051988A1|2016-04-07|Movement control device for work vehicle, and work vehicle

---

CN103810907A|2014-05-21|System and method for enhancing pilot decision making during landing in challenging weather

---

US9182760B2|2015-11-10|Method of managing a worksite

---

AU2017249116B2|2021-12-23|Driver guidance for guided maneuvering

---

CN106560347A|2017-04-12|Parking Obstruction Locator And Height Estimator

---

JP2018032343A|2018-03-01|Accident risk visualization system, accident risk visualization method, and accident risk visualization program

---

US20200249035A1|2020-08-06|Automatic Target Selection for Worksite Spotting

---

JP2022509762A|2022-01-24|Performing tasks using autonomous machines

---

US20210109538A1|2021-04-15|Restricted area autonomous vehicle control techniques

---

WO2022024120A1|2022-02-03|Guidance of a transport vehicle to a loading point

---

CN112950966A|2021-06-11|Information processing device, information processing system, and computer-readable recording medium

同族专利:

---

公开号 | 公开日

---

BR112014002503A2|2017-03-14|

---

WO2013028905A2|2013-02-28|

---

US20130054133A1|2013-02-28|

---

WO2013028905A3|2014-05-15|

---

US9157754B2|2015-10-13|

---

AU2012298792B2|2015-05-07|

---

US8583361B2|2013-11-12|

---

CA2850076C|2019-07-02|

---

AU2015210389A1|2015-09-03|

---

CA3042564A1|2013-02-28|

---

US9644978B2|2017-05-09|

---

AU2012298792A1|2014-01-16|

---

US10330481B2|2019-06-25|

---

CL2014000424A1|2014-09-05|

---

US20140100782A1|2014-04-10|

---

AU2015210389B2|2017-05-11|

---

US20170205241A1|2017-07-20|

---

AU2017213441A1|2017-08-24|

---

AU2019204471A1|2019-07-11|

---

US20190265051A1|2019-08-29|

---

ZA201400328B|2015-12-23|

---

US20150285650A1|2015-10-08|

---

US9562784B2|2017-02-07|

---

US11193774B2|2021-12-07|

---

US20150292895A1|2015-10-15|

---

CA2850076A1|2013-02-28|

引用文献:

---

公开号 | 申请日 | 公开日 | 申请人 | 专利标题

---

---

US4831539A|1984-04-27|1989-05-16|Hagenbuch Roy George Le|Apparatus and method for locating a vehicle in a working area and for the on-board measuring of parameters indicative of vehicle performance|

---

US4684247A|1985-10-18|1987-08-04|Calspan Corporation|Target member for use in a positioning system|

---

WO1995018977A1|1994-01-03|1995-07-13|Trimble Navigation|A network for code phase differential gps corrections|

---

US5675515A|1995-12-28|1997-10-07|Hunter Engineering Company|Apparatus and method for determining vehicle wheel alignment measurements from three dimensional wheel positions and orientations|

---

US6249740B1|1998-01-21|2001-06-19|Kabushikikaisha Equos Research|Communications navigation system, and navigation base apparatus and vehicle navigation apparatus both used in the navigation system|

---

US6188937B1|1998-09-30|2001-02-13|Honeywell International Inc.|Methods and apparatus for annunciation of vehicle operational modes|

---

US6225574B1|1998-11-06|2001-05-01|Harnischfeger Technology, Inc.|Load weighing system for a heavy machinery|

---

JP3654048B2|1999-05-20|2005-06-02|日産自動車株式会社|Drive control apparatus for hybrid vehicle|

---

US6418376B1|1999-08-30|2002-07-09|Johnson Controls Technology Company|Method and apparatus to maintain compass heading with a moveable sensor mounting|

---

US6157889A|1999-09-16|2000-12-05|Modular Mining Systems, Inc.|Load distribution system for haulage trucks|

---

SE521694C2|1999-09-21|2003-11-25|Kongelf Holding Ab|Vehicle movement control system|

---

US6442456B2|2000-03-07|2002-08-27|Modular Mining Systems, Inc.|Anti-rut system for autonomous-vehicle guidance|

---

US6732024B2|2001-05-07|2004-05-04|The Board Of Trustees Of The Leland Stanford Junior University|Method and apparatus for vehicle control, navigation and positioning|

---

US20110068954A1|2006-06-20|2011-03-24|Zonar Systems, Inc.|Method and apparatus to collect object identification data during operation of a vehicle and analysis of such data|

---

US6694259B2|2001-10-17|2004-02-17|Sun Microsystems, Inc.|System and method for delivering parking information to motorists|

---

KR100499002B1|2003-01-02|2005-07-01|엘지전자 주식회사|A method for searching return routes of vehicles in navigation systems|

---

FI116748B|2003-03-25|2006-02-15|Sandvik Tamrock Oy|Procedure for automatic control of a mining machine|

---

US7620202B2|2003-06-12|2009-11-17|Honda Motor Co., Ltd.|Target orientation estimation using depth sensing|

---

FI115414B|2003-07-03|2005-04-29|Sandvik Tamrock Oy|Arrangement for monitoring the location of a mine vehicle in a mine|

---

US20070138347A1|2004-12-16|2007-06-21|Ehlers Gregory A|System and method for providing information to an operator of a vehicle|

---

JP4350570B2|2004-03-23|2009-10-21|アルパイン株式会社|Navigation system, in-vehicle navigation device, and navigation information acquisition method|

---

JP4461920B2|2004-06-23|2010-05-12|株式会社デンソー|Parking assistance device|

---

US7271766B2|2004-07-30|2007-09-18|Novariant, Inc.|Satellite and local system position determination|

---

JP4665515B2|2004-12-28|2011-04-06|日産自動車株式会社|Multi-vehicle group driving support device|

---

US7731588B2|2005-09-28|2010-06-08|The United States Of America As Represented By The Secretary Of The Navy|Remote vehicle control system|

---

US7427929B2|2005-10-12|2008-09-23|Toyota Motor Engineering & Manufacturing North America, Inc.|Method and apparatus for previewing conditions on a highway|

---

US10378896B2|2006-02-27|2019-08-13|Trimble Inc.|Method and system for planning the path of an agricultural vehicle|

---

JP4604119B2|2006-03-10|2010-12-22|パイオニア株式会社|Mobility support system, method thereof, program thereof, and recording medium recording the program|

---

US9733625B2|2006-03-20|2017-08-15|General Electric Company|Trip optimization system and method for a train|

---

JP4651718B2|2006-12-04|2011-03-16|三菱電機株式会社|Navigation device|

---

US8086396B1|2006-12-07|2011-12-27|Itt Manufacturing Enterprises, Inc.|Close-spaced leader-follower navigation using control mimic|

---

US8768558B2|2007-01-05|2014-07-01|Agjunction Llc|Optical tracking vehicle control system and method|

---

US7920984B2|2007-03-15|2011-04-05|Board Of Regents Of The University Of Nebraska|Measurement of vertical track modulus using space curves|

---

DE102007039252A1|2007-08-20|2009-02-26|Siemens Ag|Guidance system for a surface mining vehicle in an open-pit area|

---

US8095248B2|2007-09-04|2012-01-10|Modular Mining Systems, Inc.|Method and system for GPS based navigation and hazard avoidance in a mining environment|

---

JP4434251B2|2007-09-25|2010-03-17|株式会社デンソー|Navigation device and program for navigation device|

---

US7782251B2|2007-10-06|2010-08-24|Trex Enterprises Corp.|Mobile millimeter wave imaging radar system|

---

AT524708T|2008-03-14|2011-09-15|Harman Becker Automotive Sys|METHOD FOR OPERATING A VEHICLE NAVIGATION SYSTEM AND VEHICLE NAVIGATION SYSTEM|

---

US8755968B2|2008-04-22|2014-06-17|Mark Gottlieb|Context-sensitive navigational aid|

---

DE102008029371A1|2008-06-20|2010-01-07|Siemens Aktiengesellschaft|Method for automatic classification of vehicle i.e. lorry, involves extracting characteristics, determining vehicle type by selecting vehicle model, and re-estimating vehicle position based on corresponding characteristics|

---

US8909466B2|2008-08-01|2014-12-09|Environmental Systems Research Institute, Inc.|System and method for hybrid off-board navigation|

---

US9235214B2|2008-09-11|2016-01-12|Deere & Company|Distributed knowledge base method for vehicular localization and work-site management|

---

US8990004B2|2008-12-17|2015-03-24|Telenav, Inc.|Navigation system with query mechanism and method of operation thereof|

---

EP2387526B1|2009-01-17|2019-08-14|Boomerang Systems, Inc.|Omnidirectional drive and steering unit|

---

US9008955B2|2009-05-05|2015-04-14|GM Global Technology Operations LLC|Route planning system for vehicles|

---

US20110106376A1|2009-10-30|2011-05-05|Louis Tijerina|System and method for automatically controlling vehicle turn signal switches|

---

EP2504663A1|2009-11-24|2012-10-03|Telogis, Inc.|Vehicle route selection based on energy usage|

---

US8970111B2|2010-03-02|2015-03-03|Evolved Aircraft Systems, L.L.C.|Method and apparatus for automatically controlling airborne vehicle lighting systems|

---

FI122157B|2010-05-10|2011-09-15|Sandvik Mining & Constr Oy|Method and equipment for mining vehicle safety equipment|

---

JP5182336B2|2010-08-02|2013-04-17|株式会社デンソー|Driving characteristic identification device and route search device|

---

JP5263243B2|2010-09-02|2013-08-14|株式会社デンソー|Vehicle display device|

---

US8645060B2|2010-09-07|2014-02-04|Qualcomm Incorporated|Positioning network availability and reliability based routing|

---

US20120078509A1|2010-09-27|2012-03-29|Honda Motor Co., Ltd|Intelligent Navigation For A Motor Vehicle|

---

US9302859B2|2010-10-04|2016-04-05|Leica Geosystems Mining, Inc.|Vehicle loading and unloading detection|

---

US20120226440A1|2011-03-02|2012-09-06|Navman Wiresless North America LP|Systems and methods for managing mobile assets using estimated time of arrival information|

---

US20120299702A1|2011-05-26|2012-11-29|Caterpillar Inc.|Hybrid positioning system|

---

US20160091325A1|2014-09-25|2016-03-31|Nissan North America, Inc.|Method and system of assisting a driver of a vehicle|WO2011124271A1|2010-04-09|2011-10-13|Tomtom International B.V.|Method of generating a route|

---

JP5202667B2|2011-02-22|2013-06-05|株式会社小松製作所|Hydraulic excavator position guidance system and control method thereof|

---

JPWO2012133410A1|2011-03-31|2014-07-28|日立建機株式会社|Positioning support system for transporting machines|

---

WO2013028221A1|2011-08-19|2013-02-28|Aerovironment Inc.|Deep stall aircraft landing|

---

WO2013062608A2|2011-08-19|2013-05-02|Aerovironment Inc.|Inverted-landing aircraft|

---

SE537371C2|2011-11-18|2015-04-14|Atlas Copco Rock Drills Ab|Method and apparatus for operating a mining and / or construction machine|

---

US8954241B2|2012-08-10|2015-02-10|Caterpillar Inc.|Mining truck spotting under a shovel|

---

US8825371B2|2012-12-19|2014-09-02|Toyota Motor Engineering & Manufacturing North America, Inc.|Navigation of on-road vehicle based on vertical elements|

---

US9244464B2|2013-01-28|2016-01-26|Caterpillar Inc.|Machine control system having autonomous edge dumping|

---

AU2015201679B2|2014-04-14|2019-06-27|Caterpillar Inc.|Operator assistance system|

---

US10228232B2|2014-04-14|2019-03-12|Caterpillar Inc.|Operator assistance system|

---

WO2014169182A2|2013-04-12|2014-10-16|Dana Limited|Vehicle and operator guidance by pattern recognition|

---

DE102013209729A1|2013-05-24|2014-11-27|Robert Bosch Gmbh|Driver assistance system with additional information about a road map|

---

CA2878018C|2013-08-20|2020-05-05|Koji Takeda|Management system and method for loading start times on haul machines|

---

CA2878098C|2013-08-20|2020-03-24|Koji Takeda|Positionally based multiple haul machine management system|

---

EP2913216B1|2013-09-27|2022-01-19|Transoft Solutions, Inc.|Method and apparatus for generating a vehicle path|

---

EP3072021A4|2013-11-21|2017-08-02|Scania CV AB|System and method to make possible autonomous operation and/or external control of a motor vehicle|

---

JP6549116B2|2013-11-30|2019-07-24|サウジ アラビアン オイル カンパニー|System and method for calculating device orientation|

---

US10102578B2|2014-03-24|2018-10-16|State Street Bank And Trust Company|Techniques for automated call cross trade imbalance execution|

---

WO2015151583A1|2014-03-31|2015-10-08|株式会社小松製作所|Mine management system|

---

US9164514B1|2014-04-14|2015-10-20|Southwest Research Institute|Cooperative perimeter patrol system and method|

---

US20150308850A1|2014-04-24|2015-10-29|Ford Global Technologies, Llc|Method and Apparatus for Contact Address Population and Verbal Address Selection|

---

US9322148B2|2014-06-16|2016-04-26|Caterpillar Inc.|System and method for terrain mapping|

---

JP6382688B2|2014-11-06|2018-08-29|日立建機株式会社|Map generator|

---

US9464913B2|2015-02-16|2016-10-11|Jaybridge Robotics, Inc.|Assistive vehicular guidance system and method|

---

DE102015004369A1|2015-04-02|2016-10-06|Audi Ag|Method for determining a suitable parking space, motor vehicle and server|

---

US9663033B2|2015-05-07|2017-05-30|Caterpillar Inc.|Systems and methods for collision avoidance using a scored-based collision region of interest|

---

KR102043060B1|2015-05-08|2019-11-11|엘지전자 주식회사|Autonomous drive apparatus and vehicle including the same|

---

WO2016183637A1|2015-05-20|2016-11-24|Optimining Pty Ltd|Vehicle monitoring|

---

US20160349754A1|2015-05-29|2016-12-01|Clearpath Robotics, Inc.|Method, system and apparatus for controlling self-driving vehicles|

---

US9719498B2|2015-05-29|2017-08-01|Caterpillar Inc.|System and method for recovering energy in a machine|

---

BR112018001309A2|2015-07-22|2018-09-11|Modular Mining Systems Inc|tire condition optimization system and method for a group of mining vehicles|

---

JP6480830B2|2015-08-24|2019-03-13|株式会社小松製作所|Wheel loader control system, control method therefor, and wheel loader control method|

---

US10281281B2|2015-09-02|2019-05-07|The United States Of America As Represented By The Secretary Of The Navy|Decision support and control systems including various graphical user interfaces configured for displaying multiple transit options for a platform with respect to hazard and objects and related methods|

---

US10077984B2|2015-09-25|2018-09-18|International Business Machines Corporation|Indoor positioning system training|

---

WO2016056677A1|2015-10-30|2016-04-14|株式会社小松製作所|Mine management system and mine management method|

---

US9754490B2|2015-11-04|2017-09-05|Zoox, Inc.|Software application to request and control an autonomous vehicle service|

---

US9878664B2|2015-11-04|2018-01-30|Zoox, Inc.|Method for robotic vehicle communication with an external environment via acoustic beam forming|

---

US9804599B2|2015-11-04|2017-10-31|Zoox, Inc.|Active lighting control for communicating a state of an autonomous vehicle to entities in a surrounding environment|

---

US9632502B1|2015-11-04|2017-04-25|Zoox, Inc.|Machine-learning systems and techniques to optimize teleoperation and/or planner decisions|

---

US9517767B1|2015-11-04|2016-12-13|Zoox, Inc.|Internal safety systems for robotic vehicles|

---

US9910441B2|2015-11-04|2018-03-06|Zoox, Inc.|Adaptive autonomous vehicle planner logic|

---

US10248119B2|2015-11-04|2019-04-02|Zoox, Inc.|Interactive autonomous vehicle command controller|

---

US9916703B2|2015-11-04|2018-03-13|Zoox, Inc.|Calibration for autonomous vehicle operation|

---

US9802661B1|2015-11-04|2017-10-31|Zoox, Inc.|Quadrant configuration of robotic vehicles|

---

US9630619B1|2015-11-04|2017-04-25|Zoox, Inc.|Robotic vehicle active safety systems and methods|

---

US10401852B2|2015-11-04|2019-09-03|Zoox, Inc.|Teleoperation system and method for trajectory modification of autonomous vehicles|

---

US9734455B2|2015-11-04|2017-08-15|Zoox, Inc.|Automated extraction of semantic information to enhance incremental mapping modifications for robotic vehicles|

---

US9606539B1|2015-11-04|2017-03-28|Zoox, Inc.|Autonomous vehicle fleet service and system|

---

US10745003B2|2015-11-04|2020-08-18|Zoox, Inc.|Resilient safety system for a robotic vehicle|

---

US10000124B2|2015-11-04|2018-06-19|Zoox, Inc.|Independent steering, power, torque control and transfer in vehicles|

---

US9958864B2|2015-11-04|2018-05-01|Zoox, Inc.|Coordination of dispatching and maintaining fleet of autonomous vehicles|

---

US9720415B2|2015-11-04|2017-08-01|Zoox, Inc.|Sensor-based object-detection optimization for autonomous vehicles|

---

US9494940B1|2015-11-04|2016-11-15|Zoox, Inc.|Quadrant configuration of robotic vehicles|

---

US10334050B2|2015-11-04|2019-06-25|Zoox, Inc.|Software application and logic to modify configuration of an autonomous vehicle|

---

US9507346B1|2015-11-04|2016-11-29|Zoox, Inc.|Teleoperation system and method for trajectory modification of autonomous vehicles|

---

US10496766B2|2015-11-05|2019-12-03|Zoox, Inc.|Simulation system and methods for autonomous vehicles|

---

US9613386B1|2015-12-01|2017-04-04|Google Inc.|Pickup and drop off zones for autonomous vehicles|

---

US9618348B1|2015-12-11|2017-04-11|Caterpillar Inc.|Spotting location system of a loading machine|

---

CN110196060A|2016-01-25|2019-09-03|上海安吉四维信息技术有限公司|A kind of working method of navigation system and vehicle based on Beidou|

---

CN105466446B|2016-01-25|2019-06-21|上海工业控制安全创新科技有限公司|A kind of navigation system, working method and the vehicle of GPS Redundancy Design|

---

CN105675001B|2016-01-25|2019-06-07|北京讯腾智慧科技股份有限公司|Split type navigation system, working method and vehicle|

---

CN105676244B|2016-01-25|2019-03-22|江苏千里马科技有限公司|A kind of portable navigation system, working method and vehicle|

---

US10403151B2|2016-02-03|2019-09-03|Caterpillar Inc.|Traffic system having congestion management|

---

US10662045B2|2016-02-11|2020-05-26|Clearpath Robotics Inc.|Control augmentation apparatus and method for automated guided vehicles|

---

CN105824038A|2016-03-14|2016-08-03|南通科技职业学院|Remote fire behavior monitoring system and working method thereof|

---

CN105807297A|2016-03-16|2016-07-27|江苏理工学院|Fire detecting, positioning and rescuing system and method based on wireless network|

---

CN105806356A|2016-03-28|2016-07-27|朱海燕|Welfare vehicle for optimizing navigation path and navigation method of welfare vehicle|

---

CN105806357A|2016-03-28|2016-07-27|朱海燕|Welcab based on navigation path optimization and navigation method thereof|

---

CN105865473A|2016-04-11|2016-08-17|钱珺佳|Cloud calculation-based driving monitoring system and working method thereof|

---

CA2953477C|2016-04-28|2020-06-02|Komatsu Ltd.|Work machine management apparatus|

---

JP6712906B2|2016-05-31|2020-06-24|株式会社小松製作所|Work machine management device, work machine, and work machine management system|

---

US10126136B2|2016-06-14|2018-11-13|nuTonomy Inc.|Route planning for an autonomous vehicle|

---

US11092446B2|2016-06-14|2021-08-17|Motional Ad Llc|Route planning for an autonomous vehicle|

---

US20170356748A1|2016-06-14|2017-12-14|nuTonomy Inc.|Route Planning for an Autonomous Vehicle|

---

US10309792B2|2016-06-14|2019-06-04|nuTonomy Inc.|Route planning for an autonomous vehicle|

---

US10829116B2|2016-07-01|2020-11-10|nuTonomy Inc.|Affecting functions of a vehicle based on function-related information about its environment|

---

KR101747375B1|2016-09-12|2017-06-15|아이피랩 주식회사|Apparatus and method for vehicle remote controlling and remote driving system|

---

US10473470B2|2016-10-20|2019-11-12|nuTonomy Inc.|Identifying a stopping place for an autonomous vehicle|

---

US10681513B2|2016-10-20|2020-06-09|nuTonomy Inc.|Identifying a stopping place for an autonomous vehicle|

---

US10331129B2|2016-10-20|2019-06-25|nuTonomy Inc.|Identifying a stopping place for an autonomous vehicle|

---

US10857994B2|2016-10-20|2020-12-08|Motional Ad Llc|Identifying a stopping place for an autonomous vehicle|

---

US9797247B1|2016-11-21|2017-10-24|Caterpillar Inc.|Command for underground|

---

US10289112B2|2016-12-16|2019-05-14|Caterpillar Inc.|Method and system for positioning a truck for loading|

---

US10585440B1|2017-01-23|2020-03-10|Clearpath Robotics Inc.|Systems and methods for using human-operated material-transport vehicles with fleet-management systems|

---

DE102017000608A1|2017-01-24|2018-07-26|Man Truck & Bus Ag|Method for operating a vehicle, in particular a utility vehicle|

---

US10338594B2|2017-03-13|2019-07-02|Nio Usa, Inc.|Navigation of autonomous vehicles to enhance safety under one or more fault conditions|

---

US10802503B2|2017-03-31|2020-10-13|Komatsu Ltd.|Control system of transporter vehicle, transporter vehicle, and control method of transporter vehicle|

---

US10640121B2|2017-04-28|2020-05-05|International Business Machines Corporation|Vehicle control for reducing road wear|

---

DE102017109731A1|2017-05-05|2018-11-08|Konecranes Global Corporation|Method and system for operating an automatically guided transport vehicle for containers|

---

US10423162B2|2017-05-08|2019-09-24|Nio Usa, Inc.|Autonomous vehicle logic to identify permissioned parking relative to multiple classes of restricted parking|

---

EP3415390A1|2017-06-12|2018-12-19|Safemine AG|Driving assistance system for reversing a mining haulage vehicle|

---

US10710633B2|2017-07-14|2020-07-14|Nio Usa, Inc.|Control of complex parking maneuvers and autonomous fuel replenishment of driverless vehicles|

---

US10369974B2|2017-07-14|2019-08-06|Nio Usa, Inc.|Control and coordination of driverless fuel replenishment for autonomous vehicles|

---

US11001446B2|2017-08-31|2021-05-11|Clearpath Robotics Inc.|Apparatus, systems, and methods for payload pick-up and drop-off with a self-driving material-transport vehicle|

---

US10380808B2|2017-09-12|2019-08-13|Deere & Company|Utilizing on-board measurements and location as inputs into load tracking|

---

US10643159B2|2017-11-20|2020-05-05|Caterpillar Inc.|System and method for mining site production planning|

---

EP3499405A1|2017-12-13|2019-06-19|My Virtual Reality Software AS|Method and device for augmenting a person's view of a mining vehicle on a mining worksite in real-time|

---

JP6766798B2|2017-12-15|2020-10-14|株式会社デンソー|Road map generation system and road map generation method|

---

US11022971B2|2018-01-16|2021-06-01|Nio Usa, Inc.|Event data recordation to identify and resolve anomalies associated with control of driverless vehicles|

---

US11189172B2|2018-03-15|2021-11-30|Modular Mining Systems, Inc.|Projected zone overlap|

---

PL430083A1|2018-06-01|2019-12-02|Joy Global Underground Mining Llc|Method and systems for steering a mining machine course|

---

US11099018B2|2018-11-27|2021-08-24|Caterpillar Inc.|Route planner for work machines|

---

CN109781132B|2019-03-14|2020-12-01|北京百度网讯科技有限公司|Experience route replacing method and device, electronic equipment and storage medium|

---

EP3764187A1|2019-07-12|2021-01-13|Safemine AG|Mining or construction vehicle assistance system|

---

US20210118066A1|2019-10-21|2021-04-22|Freeport-Mcmoran Inc.|Methods and systems for the batch delivery of material to a continuous material processor|

---

CN111091310B|2020-01-17|2020-12-08|中联重科股份有限公司|Excavation equipment health monitoring system and method|

---

AU2021204532A1|2020-03-17|2021-10-07|Freeport-Mcmoran Inc.|Methods and systems for deploying equipment required to meet defined production targets|

---

CN112013831A|2020-09-09|2020-12-01|北京易控智驾科技有限公司|Map boundary automatic extraction method and device based on terrain analysis|

---

CN112319503A|2020-09-30|2021-02-05|中国煤炭科工集团太原研究院有限公司|Vehicle control method based on coal mine trackless auxiliary transport robot|

法律状态:
2018-12-11| B06F| Objections, documents and/or translations needed after an examination request according [chapter 6.6 patent gazette]|

---

2019-12-24| B06U| Preliminary requirement: requests with searches performed by other patent offices: procedure suspended [chapter 6.21 patent gazette]|

---

2021-04-06| B09A| Decision: intention to grant [chapter 9.1 patent gazette]|

---

2021-06-01| B16A| Patent or certificate of addition of invention granted [chapter 16.1 patent gazette]|Free format text: PRAZO DE VALIDADE: 20 (VINTE) ANOS CONTADOS A PARTIR DE 23/08/2012, OBSERVADAS AS CONDICOES LEGAIS. |

优先权:

---

申请号 | 申请日 | 专利标题

---

US13/217,113|US8583361B2|2011-08-24|2011-08-24|Guided maneuvering of a mining vehicle to a target destination|

---

US13/217,113|2011-08-24|

---

PCT/US2012/052126|WO2013028905A2|2011-08-24|2012-08-23|Guided maneuvering of a mining vehicle to a target destination|

---