determining a destination of a projected path of the machine

Abstract

A machine includes an implement and a linkage mechanism, a perception sensor system including one or more perception sensors, a mechanical sensor system including one or more mechanical sensors, and a controller. The controller obtains perception information from the perception sensor system, where the perception information is indicative of respective locations of a plurality of targets. The controller obtains mechanical information from the mechanical sensor system. The controller determines respective potential paths of the machine to the plurality of targets based on the perception information and the mechanical information; determines a projected path of the machine based on the mechanical information. The controller determines that a particular target of the plurality of targets is a destination of the projected path based on the respective potential paths of the machine and the projected path of the machine.

Description

Technical Field

[0001] This disclosure generally relates to a machine, and for example to determining the destination of the machine's intended path. Background Technology

[0002] To perform a dumping operation, machinery such as wheel loaders can use implements (e.g., buckets or other implements) to load and transport materials (e.g., asphalt, debris, dirt, snow, feedstock, gravel, logs, ore, recycled materials, rocks, sand, sawdust, or similar materials) and dump the material into a dumping target (e.g., another piece of machinery, such as a dump truck). The machinery may include sensing sensors to detect the location of the dumping target in order to enable automated implement lifting operations. For example, the machinery can use sensing sensors to identify when it is sufficiently close to the dumping target and thereby automatically raise the implement to the dumping height so that once the machinery reaches the dumping target, the material can be effectively dumped from the implement into the dumping target.

[0003] However, machinery typically operates in work sites involving more than one dumping target. Therefore, in many cases, sensing sensors detect the corresponding positions of multiple dumping targets, but the machinery cannot distinguish which dumping target is its intended destination. This leads to automated implement lifting operations being performed whenever the machinery is sufficiently close to a dumping target, even when the dumping target is not the machinery's intended destination. Consequently, the implement may be lifted to a high position at inappropriate times (e.g., when the machinery is passing the first dumping target to proceed to the second), causing the machinery's center of gravity to rise (e.g., when the machinery is traveling with the implement in a high position). This can reduce the machinery's stability and control, potentially leading to spillage of material being transported by the machinery. Furthermore, when transporting heavy materials, unnecessary implement lifting can increase wear and breakage on the implement and the linkages connecting the implement to the machinery, which can affect the performance of the implement and linkages, as well as the machinery itself, and reduce its operational life.

[0004] The controller disclosed herein addresses one or more of the problems set forth above and / or other problems in the art. Summary of the Invention

[0005] In some embodiments, a machine includes: a tool and a linkage mechanism; a sensing sensor system including one or more sensing sensors; a mechanical sensor system including one or more mechanical sensors; and a controller configured to: obtain sensing information from the sensing sensor system, wherein the sensing information indicates the corresponding location of a plurality of targets; obtain mechanical information from the mechanical sensor system; determine corresponding potential paths from the machine to the plurality of targets based on the sensing information and the mechanical information; determine a predicted path for the machine based on the mechanical information; and determine, based on the corresponding potential paths and the predicted path for the machine, that a particular target among the plurality of targets is the destination of the predicted path.

[0006] In some embodiments, a controller for a machine includes one or more memories; and one or more processors coupled to the one or more memories, the one or more processors being configured to: obtain sensing information from a sensing sensor system of the machine; obtain machine information from a machine sensor system of the machine; determine, based on the sensing information and the machine information, corresponding potential paths from the machine to a plurality of targets; determine, based on the machine information, a predicted path from the machine; and determine, based on the corresponding potential paths from the machine and the predicted path from the machine, a specific target among the plurality of targets as the destination of the predicted path.

[0007] In some implementations, a method includes obtaining sensing information and mechanical information by a controller of a machine; determining, based on the sensing information and the mechanical information, corresponding potential paths from the machine to a plurality of targets; and determining, based on the corresponding potential paths and the expected paths of the machine, that a particular target among the plurality of targets is the destination of the expected path. Attached Figure Description

[0008] Figure 1 This is a diagram of the exemplary machine described in this article.

[0009] Figure 2 This is a diagram of an exemplary configuration of the front of the machine.

[0010] Figures 3A-3E This is a diagram of an exemplary embodiment described herein.

[0011] Figures 4A-4B This is a diagram of an exemplary embodiment described herein.

[0012] Figure 5 This is a diagram of an exemplary component of a device associated with determining the destination of a machine's expected path. Detailed Implementation

[0013] This disclosure relates to a controller for a machine (e.g., one that performs a dumping operation) and is applicable to any machine capable of loading and moving materials (e.g., from a first position to a second different position) and / or dumping materials (e.g., into a dumping target). For example, the machine can be any machine performing operations associated with industries such as mining, construction, agriculture, transportation, or any other industry. As some examples, the machine can be a vehicle, wheel loader, backhoe loader, cold milling machine, compactor, logging stacker, forestry machinery, timber harvester, harvester, excavator, industrial loader, boom loader, material handling machine, automatic grader, pipelaying machine, road reclaimer, skid steer loader, tractor, bulldozer, tractor-mounted scraper, or other above-ground, underground, aerial, or marine equipment.

[0014] Figure 1 This is a diagram of the exemplary machinery 100 described herein. For example, machinery 100 may include mobile machinery, such as... Figure 1 The wheel loader or any other type of mobile machinery shown. Furthermore, machinery 100 can be manned or unmanned, and / or can be fully autonomous, semi-autonomous, or remotely operated.

[0015] As shown in the figure, machinery 100 may have a frame 102 supporting an operator station 104, a power system 106, a drive system 108, implements 110, a sensing sensor system 112, and a controller 114. The operator station 104 may include operator controls 116 for operating machinery 100 via the power system 106. In some instances, machinery 100 may not include an operator station 104 and / or operator controls 116 (e.g., machinery 100 may be controlled via other means such as a remote control system). The operator station 104 may be configured to define an internal compartment 118 in which the operator controls 116 are housed.

[0016] The power system 106 is configured to supply power to the machinery 100. The power system 106 is operatively arranged to receive control signals from operator controls 116 in operator station 104 and / or from controller 114. Alternatively, the power system 106 may be operatively arranged with drive system 108 and / or implement 110 to selectively operate drive system 108 and / or implement 110 according to control signals. The power system 106 can provide operating power for the propulsion of drive system 108 and / or the operation of implement 110. The power system 106 may include an engine, motor, electric drive, fuel cell, and / or another type of power system.

[0017] Drive system 108 may be operatively arranged with power system 106 to selectively propel machinery 100 via control signals. Drive system 108 may include a plurality of ground engagement members, such as wheels 120 as shown, which are movably connected to frame 102 via axles, drive shafts and / or other components. Drive system 108 may be configured as a tracked drive system, a wheeled drive system or any other type of drive system configured to propel machinery 100.

[0018] The implement 110 can be operatively arranged with the power system 106, allowing the implement 110 to be selectively moved via control signals transmitted from operator controls 116 and / or controller 114 to the power system 106. For example... Figure 1 As shown, implement 110 can be coupled to machine 100 via linkage 122 (such as at the front 124 of machine 100). Implement 110 may also be referred to as an accessory, work tool, work implement and / or tool, and other examples. Figure 1 The implement 110 is depicted as a bucket as an example. Other embodiments may include any other suitable implement 110 for a variety of tasks, such as bulldozing, sweeping, compacting, leveling, lifting, loading, plowing and / or loosening, and other examples. Exemplary implements 110 include stump crushers, trenchers, brooms, brush cutters, cold milling machines, lawn mowers, topsoil looseners, processors, milling machines, rakes, saws, snow products, snow blowers, rudders, winches, augers, scrapers, crushers / hammers, compactors, cutters, forklifts, grader bits and end drills, grabs, blades and / or loosening machines, and other examples. As described elsewhere herein, implement 110 may include one or more electrically powered components or parts.

[0019] The sensing sensor system 112 includes one or more sensing sensors 126, which may be coupled to the machine 100, for example, at the front 124 of the machine 100. The one or more sensing sensors 126 may include sonar sensors, cameras, light detection and ranging (LIDAR) sensors and / or radio detection and ranging (RADAR) sensors, or another type of sensor used to sense the environment of the machine 100. That is, the one or more sensing sensors 126 may include at least one sensor configured to collect sensing data that may (e.g., by the controller 114) be used to determine at least one of the following: the location (e.g., its indicated distance and azimuth, and other instances) of a target (e.g., a dumping target) (such as relative to the machine 100) or the height of the target.

[0020] The controller 114 may include an electronic control module (ECM) or other computing device. As further described herein, the controller 114 may be configured to associate sensing data collected by one or more sensors of the sensing sensor system 112 with automatic control operations associated with at least one of the machinery 100 or the implement 110 and the linkage 122, and / or to perform one or more other actions.

[0021] The rear portion 128 of the machine 100 may include an engine and a transmission. The engine can be any type of engine suitable for using the machine 100 to perform the work, such as an internal combustion engine, diesel engine, gasoline engine, gas-fueled engine, etc. In other instances, the machine 100 may include another power system, such as an electric motor (e.g., a battery-powered system), a fuel cell, or another type of power system, instead of an engine. The transmission can transfer power from the engine to the drive system 108 and / or the implement 110.

[0022] The machinery may include a mechanical sensor system 130, which includes one or more mechanical sensors 132 that can be housed within the machinery 100. The one or more mechanical sensors 132 may include position sensors (e.g., a global positioning system (GPS) sensor or a local positioning system sensor) configured to determine the position (e.g., physical location) and / or orientation of the machinery 100; positioning sensors (e.g., a rotation sensor or another sensor) configured to detect the positioning of the implement 110 and the linkage 122; speed sensors configured to determine the speed of the machinery 100 (e.g., when traveling on a surface); steering angle sensors configured to determine the steering angle of the machinery 100; and / or one or more other sensors.

[0023] As mentioned above, providing Figure 1 As an example, other instances can be combined with... Figure 1 The examples described are different.

[0024] Figure 2 This is a diagram of an exemplary configuration 200 of the front portion 124 of the machine 100 (e.g., when the tooling 110 and linkage 122 extend to a “high” position, as further described herein). The sensing sensor system 112 may include one or more sensing sensors 126 positioned at various locations (e.g., on the machine 100, at the front portion 124 of the machine 100). For example, as... Figure 2 As shown, one or more sensing sensors 126 may be positioned at a first height associated with (e.g., aligned or nearly aligned) the top of operator station 104, and one or more sensing sensors 126 may be positioned at a second height associated with (e.g., aligned or nearly aligned) the wheel 120.

[0025] As mentioned above, providing Figure 2 As an example, other instances can be combined with... Figure 2 The examples described are different.

[0026] Figures 3A-3E This is a figure of the exemplary embodiment 300 described herein. Figures 3A-3B A side view of the machine 100 is shown when the implement 110 and the linkage 122 are in different positions and in different fields of view of one or more sensing sensors 126 of the sensing sensor system 112. Figure 3C-3E A top view is shown of the field of view of the machine 100 and one or more sensing sensors 126 of the sensing sensor system 112, which are determined to be the destination of the machine 100 as further described herein, and the expected path of the machine 100.

[0027] like Figure 3A As shown, implement 110 and linkage 122 can be in a "low" position (e.g., where implement 110 is aligned or nearly aligned with wheel 120). As part of an automated control operation (e.g., associated with machinery 100 or at least one of implement 110 and linkage 122), controller 114 can position implement 110 and linkage 122 in a low position. For example, as part of an automated control operation, controller 114 can (e.g., when machinery 100 is moving, such as in the forward direction) position implement 110 and linkage 122 in a low position to enable loading and / or transporting materials, such as from a first position to a second position associated with a dumping target (e.g., another piece of machinery, such as a dump truck). Figure 3A As shown, when in a low position, the tool 110 and the linkage mechanism 122 can not obstruct the field of view 302 of the first sensing sensor 126 of the sensing sensor system 112, and can obstruct the field of view 304 of the second sensing sensor 126 of the sensing sensor system 112.

[0028] like Figure 3B As shown, implement 110 and linkage 122 can be in a “high” position (e.g., where implement 110 is aligned or nearly aligned with the top of operator station 104). As part of automated control operation, controller 114 can position implement 110 and linkage 122 in a high position. For example, as part of automated control operation, controller 114 can (e.g., when machinery 100 is traveling, such as in the forward direction) position implement 110 and linkage 122 in a high position when machinery 100 is within a “dumping distance” (e.g., within a threshold distance) of the dumping target (e.g., to facilitate the impending dumping of material transported by implement 110). Figure 3BAs shown, when in a high position, the tool 110 and the linkage mechanism 122 can obstruct the field of view 302 of the first sensing sensor 126 of the sensing sensor system 112, but can not obstruct the field of view 304 of the second sensing sensor 126 of the sensing sensor system 112.

[0029] like Figure 3C-3E As shown, the machine 100 can be oriented in a specific direction (e.g., as shown in the diagram). Figure 3C-3E (As shown in the right direction). Multiple targets 306 (e.g., dumping targets) may be within the field of view 302 of the first sensing sensor 126 or the field of view 304 of the second sensing sensor 126 (shown as and referred to hereinafter as collective field of view 302 / 304). For example, as Figure 3C-3E As shown, the first target 306-A, the second target 306-B, and the third target 306-C can be within the collective field of view 302 / 304. Therefore, the controller 114 can obtain sensing information from the sensing sensor system 112 (e.g., from the first sensing sensor 126 and / or the second sensing sensor 126), which indicates the corresponding positions of the plurality of targets 306 (e.g., the corresponding positions of the first target 306-A, the second target 306-B, and the third target 306-C).

[0030] The controller 114 can (e.g., based on perceived information) determine the corresponding potential paths 308 from the machine 100 to the plurality of targets 306. For example, as Figure 3C As shown, controller 114 can determine a first potential path 308-A to a first target 306-A, a second potential path 308-B to a second target 306-B, and a third potential path 308-C to a third target 306-C. Each potential path 308 can be, for example, the optimal path to the corresponding target 306, which can be based on one or more criteria, such as distance from target 306 (e.g., “straight-line” distance from target 306, travel distance from target 306, or another type of distance), travel time to target 306 (e.g., the length of time to travel to target 306 using one or more operating features of machinery 100), and / or environmental factors related to the operation of machinery 100 (e.g., factors related to weather conditions, lighting conditions, and / or work site conditions), and other instances.

[0031] like Figure 3D As shown, controller 114 can determine the expected path 310 of machine 100. The expected path 310 can be an estimated actual path of machine 100, which can be based on mechanical information obtained by one or more mechanical sensors 132 of mechanical sensor system 130. The mechanical information can indicate, for example, the steering angle of machine 100 and / or the steering geometry of machine 100.

[0032] Then, controller 114 can (e.g., based on the corresponding potential path 308 and the projected path 310) determine that a particular target 306 is the destination 312 of the projected path 310. For example, as Figure 3E As shown, controller 114 can determine that target 306-B is destination 312 of the expected path 310. Controller 114 can use a cost function or another analysis technique to determine that a particular potential path 308 is associated with the expected path 310 (e.g., a particular potential path 308 is most similar to the expected path 310), and therefore, controller 114 can determine that destination 312 is a particular target 306 associated with a particular potential path 308.

[0033] As shown above, it provides Figures 3A-3E As an example, other instances can be combined with... Figures 3A-3E The examples described are different.

[0034] Figures 4A-4B This is a figure of the exemplary embodiment 400 described herein. Figures 4A-4B This illustrates how controller 114 determines that target 306 is the destination 312 of the expected path 310 of machine 100.

[0035] As in Figure 4A As shown by reference numeral 402 in the accompanying drawings, controller 114 can acquire sensing information. For example, controller 114 can acquire sensing information from sensing sensor system 112 (e.g., from one or more sensing sensors 126 of sensing sensor system 112). The sensing information may include corresponding sensing data collected by one or more sensing sensors 126. That is, each of the one or more sensing sensors 126 can send the sensing data collected by sensing sensor 126 (e.g., in real time or near real time) to controller 114, and therefore controller 114 can collectively receive the corresponding sensing data collected by one or more sensing sensors 126 as sensing information. The sensing information may indicate the corresponding location of multiple targets 306 (e.g., within the corresponding field of view of one or more sensing sensors 126 of sensing sensor system 112).

[0036] As indicated by reference numeral 404, controller 114 can acquire mechanical information. For example, controller 114 can acquire mechanical information from mechanical sensor system 130 (e.g., from one or more mechanical sensors 132 of mechanical sensor system 130). Mechanical information may include corresponding mechanical data collected by one or more mechanical sensors 132. That is, each of the one or more mechanical sensors 132 can send the mechanical data collected by mechanical sensor 132 (e.g., in real time or near real time) to controller 114, and therefore controller 114 can collectively receive the corresponding mechanical data collected by one or more mechanical sensors 132 as mechanical information.

[0037] Mechanical information may include, for example, mechanical state information and / or mechanical characteristic information. Mechanical state information may indicate at least one of the following: information associated with the speed of machine 100 (e.g., information indicating the speed of machine 100 and / or any derivative of the speed of machine 100), information associated with the steering angle of machine 100 (e.g., information indicating the steering angle of machine 100 and / or any derivative of the steering angle of machine 100), information associated with the orientation of machine 100 (e.g., information indicating the orientation of machine 100 and / or any derivative of the orientation of machine 100), or information associated with the position of machine 100 (e.g., information indicating the position of machine 100 and / or any derivative of the position of machine 100), and other instances. Mechanical characteristic information may indicate at least one of the following: information associated with the steering geometry of machine 100 (e.g., information indicating how the steering angle of machine 100 corresponds to the turning radius of machine 100, or other information), or information associated with one or more performance limits of machine 100 (e.g., information associated with steering speed limits, deceleration limits, acceleration limits, and / or other performance limits of machine 100), and other instances.

[0038] As indicated by reference numeral 406, controller 114 can (e.g., based on perceived information and / or mechanical information) determine a corresponding potential path 308 from machine 100 to a plurality of targets 306. For example, controller 114 can determine the distance (e.g., straight-line distance) from a target 306 (e.g., a specific target 306) based on perceived information (e.g., which indicates the corresponding location of the plurality of targets 306). The distance from target 306 can be a representative distance from target 306 to one or more sensing sensors 126, wherein the representative distance is a fused distance (e.g., an average or another type of integral or merging) associated with perceived data collected by one or more sensing sensors 126. Thus, controller 114 can determine a potential path 308 from machine 100 to target 306 based on the distance from target 306 and mechanical information. For example, controller 114 can identify mechanical state information and / or mechanical characteristic information included in the mechanical information. Therefore, the controller 114 can use mathematical curve equations (e.g., spiral equations, polynomial equations, or another type of mathematical curve equation) and cost equations (e.g., configured to tune the unconstrained parameters of the mathematical curve equations to determine the optimal path to target 306 or another type of path) to determine a potential path 308 from machine 100 to target 306 based on at least one of mechanical state information or mechanical characteristic information and the distance to the target.

[0039] As in Figure 4B As shown by reference numeral 408 in the accompanying drawings, controller 114 can (e.g., based on mechanical information) determine the expected path 310 of machine 100. To determine the expected path 310, controller 114 can determine information associated with the steering angle of machine 100 and information associated with the steering geometry of machine 100 based on the mechanical information. For example, controller 114 can identify mechanical state information and mechanical characteristic information included in the mechanical information. Controller 114 can thus determine information associated with the steering angle of machine 100 based on the mechanical state information, such as by processing (e.g., parsing and / or reading, and other instances), and / or can thus determine information associated with the steering geometry of machine 100 based on the mechanical characteristic information, such as by processing the mechanical characteristic information. Therefore, controller 114 can determine the expected path radius of machine 100 (e.g., where the steering angle of machine 100 remains constant) based on the information associated with the steering angle of machine 100 and the information associated with the steering geometry of machine 100, and can determine the expected path 310 of machine 100 based on the expected path radius of machine 100. Therefore, in some embodiments, the expected path 310 of the machine 100 (or at least a portion of the expected path 310 of the machine 100) may be a circle (or a portion of a circle) defined by the radius of the expected path.

[0040] As indicated by reference numeral 410, controller 114 can (e.g., based on the corresponding potential paths 308 of the machinery 100 to the plurality of targets 306 and the predicted paths 310 of the machinery 100) determine a specific target 306 among the plurality of targets 306. Figure 3E The second target (306-B) shown is the destination 312 of the expected path 310.

[0041] For example, controller 114 may use a cost function or another analysis technique and, based on the corresponding potential path 308 of machine 100, machine information (e.g., including machine state information and / or machine characteristic information), and the predicted path 310 of machine 100, determine a specific target 306 (e.g., Figure 3E The specific potential path 308 in the corresponding potential path 308 of the second target 306-B shown (e.g., Figure 3E The second potential path 308-B shown is associated with the expected path 310. That is, the controller 114 can determine that a particular potential path 308 is the most similar to the expected path 310 among the corresponding potential paths 308. Therefore, the controller 114 can (e.g., based on determining that a particular potential path 308 to a particular target 306 is associated with the expected path 310) determine that the particular target 306 is the destination 312 of the expected path 310. In other words, the controller 114 can determine that the particular target 306 is the destination 312 of the expected path 310 because the particular target 306 is associated with the particular potential path 308, which is associated with the expected path 310 (e.g., because the particular potential path 308 is the most similar to the expected path 310 among the corresponding potential paths 308).

[0042] As another example, controller 114 may use a cost function or another analysis technique and, based on the corresponding potential paths 308 of machine 100, machine information (e.g., including machine state information and / or machine characteristic information), and the expected path 310 of machine 100, determine that multiple potential paths 308 are associated with the expected path 310. That is, controller 114 may determine that multiple potential paths 308 are similar to or sufficiently similar to the expected path 310. Therefore, controller 114 may determine, based on the determination that multiple potential paths 308 are associated with the expected path 310 and based on perception information, the corresponding distances to multiple targets 306 (e.g., straight-line distances to multiple targets 306, travel distances to multiple targets 306, or other types of distances). Therefore, controller 114 may determine that the distance to a specific target 306 associated with a particular potential path 308 among the multiple potential paths 308 is less than or equal to the corresponding distance to one or more other targets 306 among the multiple targets 308 associated with one or more other potential paths 308 among the multiple potential paths 308. In other words, controller 114 can determine that a particular target 306 is closer to machine 100 than one or more other targets 306 among a plurality of targets 306. Therefore, controller 114 can (e.g., based on determining that the distance to the particular target 306 is less than or equal to the corresponding distance to one or more other targets 306) determine that the particular target 306 is the destination 312 of the expected path 310.

[0043] As in Figure 4B As further illustrated by reference numeral 412, controller 114 may (e.g., based on determining that a particular target 306 is the destination 312 of the expected path 310) associate the portion of the perceived information related to the particular target 306 (e.g., the portion of the perceived information indicating the location of the particular target 306) with automatic control operations. That is, controller 114 may process the portion of the perceived information associated with the particular target 306, and may not process or may exclude the processing of any other portion of the perceived information not associated with the particular target 306, in order to facilitate automatic control operations. For example, controller 114 may process the portion of the perceived information indicating the location of the particular target 306, and may not process any other portion of the perceived information not indicating the location of the particular target 306. By processing only the portion of the perceived information associated with the destination 312 of the expected path 310, the computing resources (e.g., processing resources, memory resources, communication resources, and / or power resources, and other instances) that would otherwise have been used by controller 114 to process other portions of the perceived information are saved.

[0044] Automatic control operations may be associated with at least one of machine 100 or tool 110 and linkage 122. For example, automatic control operations may cause machine 100 to travel to or from a specific target 306 (e.g., as destination 312 of the machine 100's expected path 310), and / or may (e.g., based on the proximity of machine 100 to the specific target 306) move tool 110 and linkage 122 to a specific position.

[0045] Controller 114 can repeatedly execute the statements in this document regarding... Figures 4A-4B One or more of the aforementioned operations, such as those performed at subsequent times (e.g., after the portion of the perceived information associated with a specific target 306 has been used in association with automatic control operations), are repeated. For example, controller 114 may be configured to... Figure 4A In a manner similar to that described by reference numerals 402, 404, and 406 in the accompanying drawings, additional perceptual information can be obtained from the sensing sensor system 112 and / or additional mechanical information from the mechanical sensor system 130, thereby determining other corresponding potential paths 308 from the machinery to the multiple targets 306. The controller 114 then, as described herein, [follows the instructions for use]. Figure 4B In a manner similar to that described by reference numerals 408 and 410 in the accompanying drawings, another expected path 310 of the machine 100 can be determined, and (e.g., based on other corresponding potential paths 308 and other expected paths 310) a particular target 306 among a plurality of targets 306 (e.g., which is the same as or different from a particular target 306 described elsewhere herein) can be determined as the destination 312 of the other expected path 310. Therefore, the controller 114, as described herein with respect to... Figure 4B In a manner similar to that described by reference numeral 412 in the accompanying drawings, portions of other perceived information associated with a specific target 306 can be used in conjunction with automatic control operations.

[0046] As mentioned above, providing Figures 4A-4B As an example, other instances can be combined with... Figures 4A-4B The examples described are different.

[0047] Figure 5 This is a diagram of exemplary components of a device 500 associated with determining the destination of a machine's expected path. Device 500 may correspond to a sensing sensor system 112, a controller 114, multiple sensing sensors 126, a mechanical sensor system 130, and / or multiple mechanical sensors 132. The sensing sensor system 112, controller 114, multiple sensing sensors 126, mechanical sensor system 130, and / or multiple mechanical sensors 132 may include one or more devices 500 and / or one or more components of device 500. Figure 5As shown, the device 500 may include a bus 510, a processor 520, a memory 530, an input component 540, an output component 550, and / or a communication component 560.

[0048] Bus 510 may include one or more components for wired and / or wireless communication between components of device 500. Bus 510 may connect components such as via operative coupling, communicative coupling, electronic coupling, and / or electrical coupling. Figure 5 Two or more components are coupled together. For example, bus 510 may include electrical connections (e.g., wires, traces, and / or leads) and / or wireless buses. Processor 520 may include a central processing unit, graphics processing unit, microprocessor, controller, microcontroller, digital signal processor, field-programmable gate array, application-specific integrated circuit, and / or another type of processing unit. Processor 520 may be implemented in hardware, firmware, or a combination of hardware and software. Processor 520 may include one or more processors capable of being programmed to perform one or more operations or processes described elsewhere herein.

[0049] Memory 530 may include volatile and / or non-volatile memory. For example, memory 530 may include random access memory (RAM), read-only memory (ROM), hard disk drive, and / or another type of memory (e.g., flash memory, magnetic memory, and / or optical memory). Memory 530 may include internal memory (e.g., RAM, ROM, or hard disk drive) and / or removable memory (e.g., removable via a universal serial bus). Memory 530 may be a non-transitory computer-readable medium. Memory 530 may store information related to the operation of device 500, one or more instructions, and / or software (e.g., one or more software applications). Memory 530 may include one or more memories, such as those coupled (e.g., communicatively coupled) to one or more processors (e.g., processor 520) via bus 510. The communicative coupling between processor 520 and memory 530 enables processor 520 to read and / or process information stored in memory 530 and / or store information in memory 530.

[0050] Input component 540 enables device 500 to receive input (such as user input and / or sensed input). For example, input component 540 may include a touchscreen, keyboard, keypad, mouse, button, microphone, switch, sensor, GPS sensor, GNSS sensor, accelerometer, gyroscope, and / or actuator. Output component 550 enables device 500 to provide output, such as via a display, speaker, and / or LED. Communication component 560 enables device 500 to communicate with other devices via wired and / or wireless connections. For example, communication component 560 may include a receiver, transmitter, transceiver, modem, network interface card, and / or antenna.

[0051] Apparatus 500 may perform one or more operations or processes described herein. For example, a non-transitory computer-readable medium (e.g., memory 530) may store a set of instructions (e.g., one or more instructions or code) for execution by processor 520. Processor 520 may execute the set of instructions to perform one or more operations or processes described herein. Execution of the set of instructions by one or more processors 520 causes one or more processors 520 and / or apparatus 500 to perform one or more operations or processes described herein. Hardwired circuitry may be used in place of or in combination with instructions to perform one or more operations or processes described herein. Alternatively or additionally, processor 520 may be configured to perform one or more operations or processes described herein. Therefore, the embodiments described herein are not limited to any particular combination of hardware circuitry and software.

[0052] supply Figure 5 The number and arrangement of components shown are given as examples. (Compared to...) Figure 5 Compared to the components shown, device 500 may include additional components, fewer components, different components, or components arranged differently. A set of components of device 500 (e.g., one or more components) may perform one or more functions described as being performed by another set of components of device 500.

[0053] Industrial applicability The embodiments described herein can be used with any machinery that includes a controller and a sensing sensor system that includes one or more sensing sensors, such as any machinery that utilizes implements and linkages, such as a wheel loader that includes implements and linkages to load, transport, and dump materials (e.g., into a dumping target).

[0054] The machinery may include one or more sensing sensors to detect the location of a target (e.g., a dumping target, such as a dump truck) to facilitate automated control operations (e.g., controlling the movement of the machinery or the operation of the machinery's implements and linkages, such as control relative to the target). For example, one or more sensing sensors may collect sensing information indicating the location of the target and transmit that sensing information to the machinery's controller, which then induces automated control operations performed relative to the target based on the sensing information.

[0055] However, in many cases, many targets are available, and one or more sensing sensors collect sensing information indicating the corresponding locations of multiple targets and transmit this sensing information to the machine's controller. As a result, because the controller cannot determine which target is the machine's intended destination, it causes automatic control operations to be performed whenever the machine approaches a target within a threshold distance, even when the target is not the machine's intended destination.

[0056] This can affect the performance of the machinery (e.g., due to unnecessary execution of automated control operations). For example, when automated control operations involve raising the implements (e.g., those holding material for final unloading) and linkages to a high position, the machinery's center of gravity rises. This can reduce the machinery's stability and control, potentially leading to spillage of material being transported by the machinery. Furthermore, especially when transporting heavy materials, unnecessary raising of the implements and linkages can increase wear and breakage on the implements and linkages, which can affect the performance of the implements and linkages, as well as the machinery itself, and reduce its operational life.

[0057] In some implementations, the controller of the machine may obtain sensing information (e.g., indicating the corresponding locations of multiple targets) from a sensing sensor system and mechanical information from a mechanical sensor system. The controller determines corresponding potential paths from the machine to the multiple targets based on the sensing information and the mechanical information. The controller also determines a predicted path for the machine based on the mechanical information. Therefore, the controller determines that a specific target among the multiple targets is the destination of the predicted path for the machine, based on the corresponding potential paths and the predicted path. For example, the controller may determine that a specific potential path is the one most similar to the predicted path among the corresponding potential paths, and because the specific target is associated with the specific potential path, it can be determined that the specific target is the destination of the predicted path. Therefore, the controller can use the portion of the sensing information associated with a specific target in conjunction with automatic control operations.

[0058] In this way, the machine's controller can determine that one of several targets is the destination of the machine's intended path, which would otherwise be practically impossible relying solely on sensing information collected by one or more sensing sensors. Therefore, the controller prevents or at least reduces the likelihood that the machine will erroneously perform automated control operations when approaching a target that is not its intended destination. Thus, when automated control operations include raising the implements and linkages to a high position, unnecessary lifting of the machine's implements (e.g., those holding material for final unloading) and linkages is reduced. Therefore, (e.g., by not unnecessarily raising the machine's center of gravity) the machine's stability and control are improved, which reduces the likelihood of material spillage by the implements. Additionally, reduced wear and breakage on the implements and linkages improves the performance of the implements and linkages, as well as the machine itself, and increases its operational life.

Claims

1. A machine comprising: Tools and linkage mechanisms; A sensing sensor system that includes one or more sensing sensors; A mechanical sensor system that includes one or more mechanical sensors; as well as Controller, the controller is configured to: Perception information is obtained from the perception sensor system. The perceived information indicates the corresponding location of multiple targets; Mechanical information is obtained from the mechanical sensor system; Based on the perceived information and the mechanical information, the corresponding potential paths from the machine to the multiple targets are determined; The expected path of the machine is determined based on the machine information; as well as Based on the corresponding potential paths of the machine and the expected paths of the machine, a specific target among the plurality of targets is determined to be the destination of the expected path.

2. The machine according to claim 1, wherein the controller is further configured to: Based on the determination that the specific target is the destination of the expected path, the portion of the sensing information indicating the location of the specific target is used in conjunction with an automatic control operation associated with at least one of the machine or the implement and the linkage mechanism.

3. The machine according to any one of claims 1-2, wherein, in order to determine the corresponding potential path of the machine, the controller is configured to: Identify the mechanical state information and mechanical characteristic information included in the mechanical information; Based on the perceived information, determine the distance to one of the plurality of targets; and The potential path from the machine to the target is determined using mathematical curve equations and cost functions, based on at least one of the machine state information or the machine characteristic information, and the distance to the target.

4. The machine according to any one of claims 1-3, wherein the machine condition information indicates at least one of the following: Information associated with the speed of the machine; Information associated with the steering angle of the machine; Information associated with the orientation of the machine; or Information associated with the position of the machine.

5. The machine according to any one of claims 1-4, wherein the mechanical characteristic information indicates at least one of the following: Information associated with the steering geometry of the machine; or Information associated with one or more performance limits of the machine.

6. The machine according to any one of claims 1-5, wherein, in order to determine the expected path of the machine, the controller is configured to: Identify the mechanical state information and mechanical characteristic information included in the mechanical information; Based on the mechanical state information, information associated with the steering angle of the machine is determined; Based on the mechanical characteristic information, information associated with the steering geometry of the machine is determined; The predicted path radius of the machine is determined based on information associated with the machine's steering angle and information associated with the machine's steering geometry; as well as The expected path of the machine is determined based on the expected path radius of the machine.

7. The machinery according to any one of claims 1-6, wherein, in order to determine that the specific target is the destination of the expected path, the controller is configured to: Using a cost function and based on the corresponding potential paths from the machine to the plurality of targets, the machine information, and the machine's projected path, a specific potential path to the specific target is determined to be associated with the projected path among the corresponding potential paths; and Based on the association between the specific potential path to the specific target and the projected path, the specific target is determined to be the destination of the projected path.

8. The machinery according to any one of claims 1-7, wherein, in order to determine that the specific target is the destination of the expected path, the controller is configured to: Using a cost function and based on the corresponding potential paths from the machine to the plurality of targets, the machine information, and the machine's projected path, determine that a plurality of potential paths among the corresponding potential paths are associated with the projected path; Based on the perceived information and based on determining that the plurality of potential paths are associated with the predicted path, it is determined that the distance to the specific target associated with a particular potential path among the plurality of potential paths is less than or equal to the corresponding distance to one or more other targets among the plurality of targets associated with one or more other potential paths among the plurality of potential paths; and Based on the determination that the distance to the specific target is less than or equal to the corresponding distance to one or more other targets, the specific target is determined to be the destination of the expected path.

9. A controller for a machine, comprising: One or more memory units; as well as One or more processors coupled to the one or more memories, the one or more processors being configured to: Perception information is obtained from the machine's sensing sensor system; Mechanical information is obtained from the mechanical sensor system of the machine; Based on the perceived information and the mechanical information, the corresponding potential paths from the machine to multiple targets are determined; The expected path of the machine is determined based on the machine information; as well as Based on the corresponding potential paths of the machine and the expected paths of the machine, a specific target among the plurality of targets is determined to be the destination of the expected path.

10. The controller of claim 9, wherein the one or more processors are further configured to: Based on the determination that the specific target is the destination of the expected path, the portion of the perceived information associated with the specific target is used in conjunction with automatic control operations.

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