Automatic operation system of mine dump truck without cab and whole-process operation method

Abstract

The present application belongs to the field of unmanned operation in mining area, and discloses a cabless mining dump truck automatic operation system and a full-process operation method. The automatic operation system comprises a decision layer, a planning layer and a control layer. On this basis, the full-process operation method of the mining dump truck is disclosed. The method covers the whole scene of the loading and unloading area and the road driving area while considering the obstacle avoidance in the driving state. Compared with the traditional unmanned driving scheme of the mining transport vehicle, the method meets the special operation mechanism of the cabless vehicle, is more efficient and safe, and improves the unmanned transport efficiency of the cabless mining dump truck.

Description

Technical Field

[0001] This invention belongs to the field of unmanned mining operations, specifically relating to an automatic operation system for a driverless mining dump truck and a full-process operation method. Background Technology

[0002] With the gradual advancement of national smart mine construction, unmanned driving in mining areas has become a crucial component. Current next-generation unmanned transportation primarily relies on drive-by-wire mining trucks and wide-body vehicles, whose algorithms are still based on human-centric thinking, resulting in limited improvements in carrying capacity and loading / unloading efficiency. Currently, foreign companies have completed the initial development of driverless mining dump trucks and are conducting small-scale trials, while similar models are under development in China. Considering both economic benefits and transportation costs, driverless transportation vehicles will become the mainstream approach in the future.

[0003] Current research has yielded relevant results regarding unmanned transportation using cab-less mining dump trucks. These include cab-less vehicle chassis structure design and underlying drive control algorithm design. There are also related algorithm designs for path tracking control. Existing research on cab-less vehicles can already meet the basic path tracking control requirements for unmanned driving. Furthermore, unmanned transportation in mining areas has also seen relevant research results in recent years, such as unmanned driving mode switching, gear control, and autonomous driving algorithm design. Existing research has already realized unmanned transportation operations for traditional mining trucks.

[0004] However, current unmanned operation systems for mining trucks still have certain shortcomings, such as: 1. Research on unmanned driving technology for traditional mining transport vehicles has not fully considered the motion characteristics and driving strategies of cab-less mining dump trucks, and directly applying them to the latter will not significantly improve efficiency; 2. Existing chassis drive strategies and automatic driving control strategies for cab-less transport vehicles are all considered from the perspective of chassis design or motion control, lacking upper-level targeted operational decision-making and planning, and cannot meet the needs of the entire process of mining operations. Therefore, it is necessary to develop a dedicated full-process operation system for cab-less mining dump trucks. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention proposes an automated operating system for a cabless mining dump truck and a full-process operating method.

[0006] The specific technical solution adopted in this invention is as follows:

[0007] This invention provides an automated operation system for a driverless mining dump truck, comprising: a decision layer that determines the current main state of the vehicle based on perceived information and determines in real time whether obstacle avoidance is required;

[0008] The planning layer plans the corresponding driving path based on the main state.

[0009] The control layer determines whether to control forward or reverse driving based on the state decided by the decision layer and the path planned by the planning layer, and outputs the corresponding control quantity.

[0010] Furthermore, the decision-making layer determines the driving area through location information, obtains the main state, and combines environmental information to determine whether to avoid obstacles;

[0011] The main state refers to the different driving states of the vehicle corresponding to each location area when the vehicle travels through different location areas; the main state includes the loading area, the road driving area, and the unloading area.

[0012] When a vehicle is in a road driving area and encounters an obstacle, it first judges the boundary information. If the distance to the boundary is less than a safety threshold, it avoids the obstacle and stops. If it is greater than the safety threshold, it judges the obstacle information. If it is judged to be a static obstacle or a low-speed obstacle, it judges whether the driving area meets the planning conditions. If it does, it performs obstacle avoidance planning; otherwise, it avoids the obstacle and stops. If it is judged to be a dynamic obstacle, it maintains a safe distance from the target obstacle and drives until no obstacle is detected, then drives at normal speed.

[0013] When a vehicle is in the loading or unloading area, if an obstacle is detected or the vehicle's distance from the loading or unloading area boundary is less than a certain threshold, the vehicle will be stopped as an obstacle avoidance vehicle.

[0014] Furthermore, the sub-states of the road driving area include unloaded forward driving and fully loaded reverse driving;

[0015] The sub-states of the loading area include forward entry, waiting, forward loading, loading operation, and reverse exit. After the main state jumps from the road driving area to the loading area, the sub-state is forward entry. After reaching the pre-stop position, it jumps to waiting. After completing the path planning from the pre-stop position to the loading point, it jumps to forward loading. After reaching the loading point, it jumps to loading operation. After loading is completed, it jumps to reverse exit. After leaving the loading area, the main state jumps back to the road driving area, and the sub-state becomes fully loaded reverse driving.

[0016] The sub-states of the unloading area include reverse entry, waiting, reverse unloading, unloading operation, and forward exit. After the main state jumps from the road driving area to the unloading area, the sub-state is reverse entry. After reaching the pre-stop position, it jumps to waiting. After completing the path planning from the pre-stop position to the unloading point, it jumps to reverse unloading. After reaching the unloading point, it is unloading operation. After completing unloading, it jumps to forward exit. After leaving the loading area, the main state jumps to the road driving area, and the sub-state becomes empty forward driving.

[0017] Furthermore, the planning layer performs corresponding planning based on the decision master state machine and sub-state machine information, including obstacle avoidance planning, loading area planning and unloading area planning;

[0018] The obstacle avoidance planning: When a static obstacle or a low-speed dynamic obstacle is detected ahead, the decision jumps to the obstacle avoidance planning state. At this time, the planning layer performs a main path offset based on the safe distance judged by the decision layer. The offset value is the safe distance divided by 2, and a smooth transition is performed using a fifth-order polynomial with the current point as the reference.

[0019] The loading area planning includes forward driving planning from the pre-parking position to the loading position and reverse driving planning from the loading position to the loading area; Dubins curves are used to achieve path planning through tangents and arcs;

[0020] The unloading area planning includes reverse driving planning from the pre-parking position to the unloading position and forward and reverse driving planning from the loading position to the loading area. Dubins curves are used to achieve path planning through tangents and arcs.

[0021] Furthermore, the control layer determines whether to perform forward or reverse driving control based on the main state determined by the decision layer and the planned path issued by the planning layer, and outputs the corresponding control quantity.

[0022] The forward driving control employs a pure tracking plus heading deviation compensation control algorithm. During forward driving, the front wheels steer while the rear wheels do not receive steering commands. The center of the vehicle's rear axle is used as the current point, and the calculation formula is as follows:

[0023]

[0024] The reverse driving control uses a pure tracking plus heading deviation compensation control algorithm, with a heading angle deviation plus 180°. During reverse driving, only the rear wheels are steered; no steering commands are issued to the front wheels. The center of the vehicle's front axle is used as the current point, and the calculation formula is as follows:

[0025]

[0026] In the formula, δ is the output front wheel steering angle, in degrees; l d The distance between the current position and the target point is the straight-line distance. The target point is indexed along a pre-collected path according to different vehicle speeds; π is pi; α is the azimuth deviation between the current point and the target point, in radians; k is the heading angle deviation compensation coefficient; β is the heading angle deviation between the current point and the target point, in radians; R2D is the radian switching angle coefficient.

[0027] This invention also provides a fully automated operation method for a cab-less mining dump truck, which uses the aforementioned fully automated operation system for cab-less mining dump trucks to perform automated operations, including the following steps:

[0028] S1. Preliminary preparation: Collect the main path, loading area, and unloading area boundaries of the entire mining operation as basic map path information; determine the unloading position in the unloading area and the directional planning range of the loading area; install and debug sensors for sensing environmental information, and the environmental information output by the sensors includes boundary information and obstacle information.

[0029] S2, driving empty in the road driving area, headed towards the loading area;

[0030] S3, arrive at the loading area, carry out loading operations, and drive out of the loading area after loading is completed;

[0031] S4, fully loaded, drives in the road driving area toward the unloading area;

[0032] S5, arrive at the unloading area, carry out the unloading operation, and drive out of the unloading area after the unloading is completed;

[0033] S6. After a single loading-unloading task is completed, the vehicle returns from the unloading area to the road driving area. During the unloaded driving process in the road driving area, if a task completion command is received from the platform, the state switch is exited, the steering wheel is turned back to the center, and the vehicle speed gradually decreases to 0 until it stops; otherwise, the main state switch logic is followed and the operation continues.

[0034] Furthermore, in step S2, the vehicle travels in the road driving area unloaded and in the forward direction, where the direction of unloading the bucket is the rear of the vehicle and the other end is the front of the vehicle. When the front of the vehicle is in front, it is in the forward direction, and when the rear of the vehicle is in front, it is in the reverse direction.

[0035] The decision-making layer combines location and environmental information to determine the main state as a road driving zone. The planning layer generates a data collection path that satisfies the motion constraints of a driverless vehicle based on the main state of the road driving zone determined by the decision-making layer. The control layer updates the vehicle parameters and performs tracking control based on the path and location information from the planning layer. At the same time, it calculates the distance to the boundary in real time and switches the corresponding state based on obstacle detection information.

[0036] Furthermore, step S3 includes the following sub-steps:

[0037] S31, the decision-making level determines whether to enter the loading pre-stop position from the road driving area. If the determination is yes, drive forward into the loading pre-stop position. After entering the loading pre-stop position, determine whether it is allowed to enter the loading point. If yes, continue to execute; otherwise, continue to wait.

[0038] S32, the planning layer plans the path from the pre-loading dock to the loading point based on the specified loading point, and sends it to the control layer to control the vehicle to reach the loading point;

[0039] S33, after loading is completed, the planning layer plans the exit path from the loading point in reverse and sends it to the control layer;

[0040] S34, the control layer receives the departure planning information, processes the positioning information and departure command, tracks the vehicle, and leaves the loading area;

[0041] S35, in the main state of the loading area, when an obstacle is detected, the vehicle will directly avoid the obstacle and stop without judging whether to detour, until no more obstacles are detected, and then switch to normal driving; and if the distance between the vehicle and the road boundary is less than a safety threshold, the vehicle will avoid the obstacle and stop.

[0042] Furthermore, in step S4, the vehicle travels in the opposite direction with a full load in the road driving area; the decision layer determines the main state as the road driving area by combining the location information and environmental information; the planning layer generates a collection path that satisfies the motion constraints of the driverless vehicle based on the main state of the road driving area determined by the decision layer; the control layer updates the vehicle parameters and performs tracking control based on the path and location information of the planning layer, while simultaneously calculating the distance to the boundary in real time and switching the corresponding state based on the obstacle detection information.

[0043] Furthermore, step S5 includes the following sub-steps:

[0044] S51, the decision-making level determines whether to enter the unloading pre-stop position from the road driving area. If the determination is yes, then drive in the opposite direction to enter the designated stop position; after entering the unloading area pre-stop position, determine whether it is allowed to enter the unloading point. If yes, continue to execute; otherwise, continue to wait.

[0045] S52, the planning layer plans the driving route from the unloading pre-stop position to the designated unloading point based on the specified unloading point, and sends the driving route to the control layer for tracking and control to ensure the vehicle reaches the unloading point;

[0046] S53, after unloading is completed, the planning layer plans the exit path from the unloading point in the forward direction and sends it to the control layer;

[0047] S54, the control layer receives the planning information, and based on the location information and the planning layer path, it tracks and controls the vehicle to leave the unloading area;

[0048] S55, in the main state of the unloading zone, when an obstacle is detected, it directly avoids the obstacle and stops without judging whether to detour, until no more obstacles are detected, and then resumes normal driving; and if the distance between the vehicle and the road boundary is less than a safety threshold, it avoids the obstacle and stops.

[0049] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0050] 1. This invention provides a fully automated operating system for cab-less mining dump trucks, which considers obstacle avoidance during driving while covering all operating scenarios in both loading / unloading areas and road driving areas. Compared to traditional unmanned mining transport vehicle solutions, it meets the special operating mechanisms of cab-less vehicles, is more efficient and safer, and improves the unmanned transportation efficiency of cab-less mining dump trucks.

[0051] 2. The fully automatic operation system for a driverless mining dump truck in this invention proposes a path tracking control method suitable for bidirectional driving, taking into account the motion characteristics of the driverless mining dump truck. By switching the current point and processing the heading angle, forward driving control and reverse driving control are achieved while ensuring the control accuracy of the original control algorithm, thereby improving the scene adaptability of the driverless mining dump truck under unmanned driving conditions.

[0052] 3. The fully automated operation method for a driverless mining dump truck in this invention adopts a fully automated operation system for a driverless mining dump truck in this invention, which includes decision planning for operation sections such as entering and exiting the loading and unloading area and loading and unloading operations; the decision method takes into account the bidirectional driving characteristics of driverless vehicles, simplifies the unmanned transportation operation process in the loading and unloading area, and reduces unnecessary condition judgment state switching.

[0053] In addition, during the planning of the loading area, the target point parameters are optimized based on the existing planning methods to reduce planning time and increase the planning success rate; thus improving the operational efficiency of the loading and unloading area for driverless mining dump trucks. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the embodiments will be briefly described below. Referring to the accompanying drawings will provide a clearer understanding of the features and advantages of the present invention. The drawings are illustrative and should not be construed as limiting the present invention in any way. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort. Wherein:

[0055] Figure 1 This is a schematic diagram of the overall logic of the present invention;

[0056] Figure 2 This is a schematic diagram of the state machine switching of the decision layer in this invention;

[0057] Figure 3 This is a schematic diagram of the loading area operation according to the present invention;

[0058] Figure 4 This is a schematic diagram of the road driving area operation according to the present invention;

[0059] Figure 5 This is a schematic diagram of the unloading area operation of the present invention;

[0060] Figure 6 This is a schematic diagram of a direction reference in one embodiment of the present invention. Detailed Implementation

[0061] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other.

[0062] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0063] Example 1

[0064] like Figure 1-5 As shown, the fully automated operation system for a driverless mining dump truck of the present invention is divided into upper-level decision-making and lower-level planning and control. The decision-making layer divides the transportation process into three main states: loading area, road driving area (including empty driving and fully loaded driving), and unloading area, with corresponding sub-states below them; the planning layer has different planning and control strategies corresponding to different decision-making states.

[0065] Specifically:

[0066] See attached document Figure 1 As shown, an automated operating system for a driverless mining dump truck includes a decision-making layer, a planning layer, and a control layer.

[0067] The decision-making level determines the current loading area, unloading area, or road driving area of ​​the vehicle by using positioning data and other sensor perception information, and makes a real-time judgment on whether obstacle avoidance is required.

[0068] The planning layer performs loading area planning, unloading area planning, obstacle avoidance planning, and other driving path planning based on the decision-making layer's main state.

[0069] The control layer performs corresponding path tracking control based on forward and reverse driving to achieve automatic operation of driverless vehicles in mining areas.

[0070] More specifically:

[0071] At the decision-making level, when the autonomous driving algorithm begins execution, the decision-making level needs to determine the driving area using location information and combine it with environmental information to determine whether to avoid obstacles and what obstacle avoidance strategy to employ.

[0072] 1) Main state judgment: The main state is divided into road driving area, loading area and unloading area, and different planning and control strategies are used for different areas.

[0073] During path acquisition, the state switching point is determined based on the boundaries of the loading and unloading areas. The distance between the actual position and the point is calculated during the journey. When the distance is less than a certain value, it is determined that the area has been entered, and the state machine switches and jumps.

[0074] This embodiment uses the entry from the road driving area into the loading area as an example. During vehicle travel, the distance between the vehicle and the loading entry point (the designated parking position within the pre-parking area) continuously decreases. When the distance is less than 0.5m, it is determined that the vehicle has entered the loading area (loading waiting area), and the state machine transitions. During this process, if an obstacle is detected, the obstacle avoidance driving state will transition at any time based on the specific judgment conditions.

[0075] 2) Obstacle avoidance driving sub-state switching: First, boundary information is judged. If the distance to the boundary is less than the safety threshold, obstacle avoidance and stopping are performed. If it is greater than the safety threshold, obstacle information is judged. If it is judged to be a static obstacle or a low-speed obstacle, it is judged whether the driving area meets the planning conditions. If it meets the conditions, obstacle avoidance planning is performed; otherwise, obstacle avoidance and stopping are performed. If it is judged to be a dynamic obstacle, a safe distance from the target obstacle is maintained until no obstacle is detected, and then driving at normal speed is performed. The specific formula is as follows:

[0076]

[0077] In the formula, `case` represents the obstacle avoidance strategy: 0 for no action (normal driving), 1 for obstacle avoidance and stopping, 2 for obstacle avoidance planning, and 3 for obstacle avoidance following; `lat_dis` is the lateral distance between the vehicle and the road boundary (in meters); `safe_dis` is the safe distance between the vehicle and the obstacle ahead (in meters); `lon_speed` is the speed of the obstacle ahead (in km / h). `not_plan` is a flag indicating that planning is not possible; 0 indicates planning is possible, and 1 indicates not planning is possible.

[0078] In addition, in this embodiment, considering the limited area of ​​the loading and unloading area, obstacle avoidance planning is not considered in the loading and unloading area. If an obstacle or vehicle is detected that is less than a certain threshold from the boundary of the loading and unloading area, it will be treated as obstacle avoidance parking.

[0079] 3) Refer to Appendix Figure 2 and 4 As shown, the road driving area sub-state switching includes empty forward driving and fully loaded reverse driving (i.e., returning to unload after loading); among them, as shown in the attached... Figure 6 As shown, the unloading direction of the bucket is defined as the rear of the vehicle, and the other end is the front of the vehicle. When the vehicle is in front, it is in the forward direction, and when the vehicle is in front, it is in the reverse direction. In this embodiment, unloaded forward driving refers to the process of the vehicle traveling towards the loading area when it is unloaded, and fully loaded reverse driving refers to the process of the vehicle traveling towards the unloading area after it has finished loading in the loading area.

[0080] 4) Refer to Appendix Figure 2 and3 As shown, the loading area sub-state switching includes forward entry, waiting, forward loading, loading operation, and reverse exit. After the main state jumps from the road driving area to the loading area, it becomes forward entry. After reaching the pre-stop position, it jumps to waiting. After completing the route planning, it jumps to forward loading. After reaching the loading point, it jumps to loading operation. After loading is completed, it becomes reverse exit. After leaving the loading area, the main state jumps back to the road driving area, and the sub-state becomes fully loaded reverse driving.

[0081] 5) Refer to Appendix Figure 2 and 5 As shown, the unloading area's sub-states switch, including reverse entry, waiting, reverse unloading, unloading operation, and forward exit. After the main state transitions from the road driving area to the unloading area, the sub-state is reverse entry. Upon reaching the pre-stop position, it transitions to waiting, then to reverse unloading after completing route planning, then to unloading operation upon reaching the unloading point, and finally to forward exit after completing unloading. After leaving the loading area, the main state transitions back to the road driving area, and the sub-state changes to empty forward driving.

[0082] Planning Layer: The planning layer needs to perform corresponding planning based on the information from the decision master state machine and sub-state machines. The target path for the road driving area is pre-collected and does not require planning. Therefore, the planning layer mainly includes obstacle avoidance planning, loading area planning, and unloading area planning.

[0083] 1) Obstacle Avoidance Planning: When a static obstacle or a low-speed dynamic obstacle is detected ahead, the state decision jumps to the obstacle avoidance planning state. At this time, the planning layer makes a main path offset based on the safe distance judged by the decision layer. The offset value is the safe distance divided by 2, and a smooth transition is made with the current point as the reference using a fifth-order polynomial.

[0084] 2) Loading Area Planning: Loading area planning includes forward travel planning from the pre-parking position to the loading position and reverse travel planning from the loading position out of the loading area. Since the planning process does not involve changing the travel direction (i.e., entering is always forward, and exiting is always reverse), Dubins curves can be used directly, with path planning achieved through tangents and arcs. (See attached diagram.) Figure 3 As shown, the target destination heading from the pre-parking position to the loading position is opposite to the heading of a traditional transport vehicle; while when driving out, the heading of the vehicle's starting position in the opposite direction is opposite to the actual heading.

[0085] During the process, the heading at the loading point is basically the same as the heading when entering the vehicle, and there is no need to reverse throughout the entire process. Compared with forward-reverse planning, this planning method allows for direct forward entry and is less restricted by the site conditions.

[0086] 3) Unloading area planning: Refer to Appendix Figure 5As shown, the unloading area planning includes reverse driving planning from the pre-parking position to the unloading position and forward driving planning from the unloading position to the unloading area. Since the planning process does not involve changing driving direction (i.e., entering is always reverse, and exiting is always forward), Dubins curves can be directly used, with path planning achieved through tangents and arcs. (See attached diagram.) Figure 5 As shown, the target destination heading from the pre-parking position to the unloading position is the same as that of a traditional transport vehicle; while when driving out, since the vehicle body posture is the same as that of a traditional transport vehicle, the driving out planning is planned normally according to the Dubins curve.

[0087] Control layer: The control layer determines whether to control forward or reverse driving based on the decision state and the path issued by the planning layer, and outputs the corresponding control quantity.

[0088] 1) Forward Driving Control: Forward driving employs a pure tracking control algorithm with heading deviation compensation, ensuring stability on straightaways while improving cornering control accuracy. During forward driving, only the front wheels are steered; no steering commands are issued to the rear wheels. The center of the vehicle's rear axle is used as the current point, and the specific formula is as follows:

[0089]

[0090] In the formula, δ is the output front wheel steering angle, in degrees; l d The distance between the current position and the target point is calculated as a straight line distance. The target point is indexed along a pre-collected path based on different vehicle speeds. α is the azimuth deviation between the current point and the target point, in radians. k is the heading angle deviation compensation coefficient, selected based on the actual tracking effect; here, 0.4 is chosen. β is the heading angle deviation between the current point and the target point, in radians. R2D is the radian switching angle coefficient; in this embodiment, R2D is set to 57.29578.

[0091] 2) Reverse Driving Control: Reverse driving employs a control algorithm that combines pure tracking with heading deviation compensation. The heading angle deviation in the pure tracking formula is increased by 180°. During reverse driving, only the rear wheels are steered; no steering commands are issued to the front wheels. The center of the vehicle's front axle is used as the current point. The specific formula is as follows:

[0092]

[0093] The symbols in the formula are consistent with those in forward driving control.

[0094] Example 2

[0095] See attached document Figure 1-5 This embodiment, based on the automated operation system disclosed in Embodiment 1, discloses a fully automated operation method for a driverless mining dump truck, which utilizes the aforementioned automated operation system. The operation segments of the entire mining process include an empty road travel segment, a loading segment, a fully loaded road travel segment, and an unloading segment.

[0096] In this embodiment, a task flow is illustrated by a driverless transport vehicle traveling from the road driving area (empty) to the loading area for loading, then traveling fully loaded to the unloading area for unloading, and finally returning to the road driving area:

[0097] S1: Preliminary preparation: Collect the main operation path of the entire mining area and the boundaries of the loading and unloading areas as basic map path information; determine the unloading position in the unloading area, and determine the locating area of ​​the loading area (the actual working range of the electric shovel used for loading and unloading materials) based on the working range of the electric shovel. Install and debug the sensing sensors, which can output environmental information (including boundary information and obstacle information), etc.

[0098] S2: Road driving area (empty, forward driving), heading towards the loading area.

[0099] S21: When the vehicle starts, the decision layer determines the main state by combining the location information and the environmental information. The planning layer issues a collection path that meets the motion constraints of the driverless vehicle based on the main state of the decision layer. The control layer performs tracking control based on the path and location information of the planning layer, while calculating the distance to the boundary in real time and switching the corresponding state based on the obstacle detection information.

[0100] The vehicle senses environmental information and enters obstacle avoidance mode if it detects an obstacle during driving: first, it determines whether the distance between the vehicle and the obstacle is greater than the preset safe distance; if it is less than the safe distance, it avoids the obstacle and stops.

[0101] If the distance is greater than the safe distance, it is determined whether the obstacle is a static obstacle or a low-speed obstacle (the low-speed obstacle refers to an obstacle with a speed lower than the preset speed, also called a "safely overtakeable obstacle"). If the obstacle is determined to be a static obstacle or a low-speed obstacle, it is determined whether to bypass the obstacle based on the motion model of the driverless vehicle. If it is determined that it can bypass the obstacle, it will bypass the obstacle. If it is determined that it cannot bypass the obstacle, it will avoid the obstacle and stop.

[0102] In this embodiment, the safe distance is ≥8m, and the low-speed obstacle is defined as having a speed of less than 5km / h. Dynamic obstacles (also called "unsafe overtakeable obstacles") have a speed of ≥5km / h in this embodiment.

[0103] S3: Loading Area

[0104] S31: The decision-making level determines whether to enter the loading pre-stop position from the road driving area. If the determination is yes, then enter the loading pre-stop position. After entering the loading pre-stop position, it determines whether it is allowed to enter the loading point. If the determination is yes, then continue execution; otherwise, continue waiting.

[0105] S32: See Appendix Figure 3Upon reaching the loading point, the planning layer directly plans a forward driving path to the loading point based on the designated loading point (this method differs from the traditional forward-reverse path of transport vehicles, as shown in the attached diagram). Figure 3 (As shown by the two curves that intersect on the right), and then send the information to the control layer to control the vehicle to reach the loading point.

[0106] S33: After loading is completed, the planning layer plans the exit path in the opposite direction, at which point the vehicle's driving direction is opposite to its entry direction.

[0107] Since the vehicle-mounted inertial navigation system cannot change direction, some of the positioning data needs to be processed.

[0108] S34: After receiving the planning information, the processed positioning information, and the departure command, the control layer performs front and rear axle switching and tracking control to drive out of the loading area.

[0109] S35: During loading, if an obstacle is detected, the vehicle will stop directly to avoid it without having to determine whether to detour, until no obstacle is detected, at which point normal driving will resume; and if the distance between the vehicle and the road boundary is less than a safety threshold, the vehicle will stop to avoid it.

[0110] S4: Road driving area (fully loaded, driving in the opposite direction)

[0111] S41: The decision-making layer determines the main state based on the location and environmental information. The planning layer determines the collected path in the road driving area that meets the motion constraints of the driverless vehicle based on the main state of the decision-making layer. The control layer performs tracking control based on the path and location information of the planning layer, while calculating the distance to the boundary in real time and switching the corresponding state based on the obstacle detection information.

[0112] It senses environmental information and enters obstacle avoidance mode if it detects an obstacle during driving. For static or low-speed obstacles, it determines whether it can avoid the obstacle based on the motion model of the driverless vehicle. When encountering dynamic obstacles, it maintains a safe distance.

[0113] S5: Unloading Area

[0114] S51: The decision-making level determines whether to enter the unloading pre-stop position from the road driving area. If it does, it enters the designated pre-stop position and determines whether to allow entry into the unloading point. If it determines that driving is allowed, it continues to execute; otherwise, it continues to wait.

[0115] S52: Entering the unloading point, the planning layer, based on the designated unloading point, differs from the traditional forward-reverse movement of transport vehicles (as shown in the attached diagram). Figure 5 As shown by the two curves converging on the right, the planning layer performs reverse unloading planning and sends the path to the control layer for tracking and control to reach the unloading point.

[0116] S53: After unloading is completed, the planning layer plans the exit path for forward driving.

[0117] S54: The control layer receives planning information and drives out of the unloading area.

[0118] If an obstacle is detected in the unloading area, the vehicle will directly avoid the obstacle and stop without needing to determine whether to detour, until no obstacle is detected, at which point it will resume normal driving; and if the distance between the vehicle and the road boundary is less than a safety threshold, the vehicle will avoid the obstacle and stop.

[0119] S6: After a single loading-unloading task is completed, the vehicle returns from the unloading area to the road driving area. During the unloaded driving process in the road driving area, if a task completion command is received from the platform, the state switch is exited, the steering wheel is turned back to center, and the vehicle speed gradually decreases to 0 until it stops; otherwise, the main state switch logic is followed and the operation continues.

[0120] Furthermore, the foregoing only describes some embodiments, and changes, modifications, additions, and / or variations can be made without departing from the scope and spirit of the disclosed embodiments. These embodiments are illustrative and not restrictive. Moreover, the described embodiments relate to those currently considered most practical and preferred, and should be understood as not being limited to the disclosed embodiments, but rather intended to cover different modifications and equivalent arrangements included within the spirit and scope of those embodiments. Furthermore, the various embodiments described above can be used in conjunction with other embodiments; for example, an aspect of one embodiment can be combined with an aspect of another embodiment to implement yet another embodiment. Additionally, individual features or components of any given component can constitute another embodiment.

[0121] The foregoing description of embodiments is provided for illustrative and explanatory purposes and is not intended to be exhaustive or limiting of this disclosure. Elements or features of a particular embodiment are generally not limited to that particular embodiment, but where applicable, elements or features are interchangeable and can be used in alternative embodiments, and can be modified in various ways, even if not specifically shown or described. Such modifications are not considered a departure from this disclosure, and all such modifications are included within the scope of this disclosure.

[0122] Therefore, it should be understood that the accompanying drawings and description provided herein by way of example are intended to aid in the understanding of the invention and should not be construed as limiting its scope.

Claims

1. An automated operating system for a cabless mining dump truck, characterized in that, include: The decision-making level determines the current main state of the vehicle based on the perceived information and makes real-time judgments on whether obstacle avoidance is necessary. The planning layer plans the corresponding driving path based on the main state. The control layer determines whether to control forward or reverse driving based on the main state decided by the decision layer and the path planned by the planning layer, and outputs the corresponding control quantity. The control layer determines whether to control forward or reverse driving based on the main state judged by the decision layer and the planned path issued by the planning layer, and outputs the corresponding control quantity. The forward driving control employs a pure tracking plus heading deviation compensation control algorithm. During forward driving, the front wheels steer while the rear wheels do not receive steering commands. The center of the vehicle's rear axle is used as the current point, and the calculation formula is as follows: The reverse driving control uses a pure tracking plus heading deviation compensation control algorithm, with a heading angle deviation plus 180°. During reverse driving, only the rear wheels are steered; no steering commands are issued to the front wheels. The center of the vehicle's front axle is used as the current point, and the calculation formula is as follows: In the formula, Outputs the front wheel steering angle, in degrees; To determine the straight-line distance between the current location and the target point, the target point is indexed along a pre-collected path based on different vehicle speeds; Pi; The azimuth deviation between the current point and the pre-aiming point, in radians; The heading angle deviation compensation coefficient; R2D represents the deviation of the heading angle between the current point and the pre-aiming point, in radians; R2D is the radian switching angle coefficient.

2. The automatic operating system for a cabless mining dump truck according to claim 1, characterized in that, The decision-making layer determines the driving area through location information, obtains the main state, and combines environmental information to determine whether to avoid obstacles. The main state refers to the different driving states of the vehicle corresponding to each location area when the vehicle travels through different location areas; the main state includes the loading area, the road driving area, and the unloading area. When a vehicle is in a road driving area and encounters an obstacle, it first judges the boundary information. If the distance to the boundary is less than a safety threshold, it avoids the obstacle and stops. If it is greater than the safety threshold, it judges the obstacle information. If it is judged to be a static obstacle or a low-speed obstacle, it judges whether the driving area meets the planning conditions. If it does, it performs obstacle avoidance planning; otherwise, it avoids the obstacle and stops. If it is judged to be a dynamic obstacle, it maintains a safe distance from the target obstacle and drives until no obstacle is detected, then drives at normal speed. When a vehicle is in the loading or unloading area, if an obstacle is detected or the vehicle is less than a certain threshold from the boundary of the loading or unloading area, it will be handled as an obstacle avoidance parking.

3. The automatic operating system for a cabless mining dump truck according to claim 2, characterized in that, The sub-states of the road driving area include unloaded forward driving and fully loaded reverse driving; The sub-states of the loading area include forward entry, waiting, forward loading, loading operation, and reverse exit. After the main state jumps from the road driving area to the loading area, the sub-state is forward entry. After reaching the pre-stop position, it jumps to waiting. After completing the path planning from the pre-stop position to the loading point, it jumps to forward loading. After reaching the loading point, it jumps to loading operation. After loading is completed, it jumps to reverse exit. After leaving the loading area, the main state jumps back to the road driving area, and the sub-state becomes fully loaded reverse driving. The sub-states of the unloading area include reverse entry, waiting, reverse unloading, unloading operation, and forward exit. After the main state jumps from the road driving area to the unloading area, the sub-state is reverse entry. After reaching the pre-stop position, it jumps to waiting. After completing the path planning from the pre-stop position to the unloading point, it jumps to reverse unloading. After reaching the unloading point, it is unloading operation. After completing unloading, it jumps to forward exit. After leaving the loading area, the main state jumps to the road driving area, and the sub-state becomes empty forward driving.

4. The automatic operating system for a cabless mining dump truck according to claim 1, characterized in that, The planning layer performs corresponding planning based on the decision master state machine and sub-state machine information, including obstacle avoidance planning, loading area planning and unloading area planning; The obstacle avoidance planning: When a static obstacle or a low-speed dynamic obstacle is detected ahead, the decision jumps to the obstacle avoidance planning state. At this time, the planning layer performs a main path offset based on the safe distance judged by the decision layer. The offset value is the safe distance divided by 2, and a smooth transition is performed using a fifth-order polynomial with the current point as the reference. The loading area planning includes a forward driving plan from the pre-parking position to the loading position and a reverse driving plan from the loading position to the loading area. Path planning is achieved using Dubins curves, tangents, and arcs. The unloading area planning includes reverse driving planning from the pre-parking position to the unloading position and forward and reverse driving planning from the loading position to the loading area. Dubins curves are used to achieve path planning through tangents and arcs.

5. A fully automated operation method for a cab-less mining dump truck, characterized in that, The automatic operation of the cabless mining dump truck automatic operation system as described in any one of claims 1-4 includes the following steps: S1. Preliminary preparation: Collect the main path, loading area, and unloading area boundaries of the entire mining operation as basic map path information; determine the unloading position in the unloading area and the directional planning range of the loading area; install and debug sensors for sensing environmental information, and the environmental information output by the sensors includes boundary information and obstacle information. S2, driving empty in the road driving area, headed towards the loading area; S3, arrive at the loading area, carry out loading operations, and drive out of the loading area after loading is completed; S4, fully loaded, drives in the road driving area toward the unloading area; S5, arrive at the unloading area, carry out the unloading operation, and drive out of the unloading area after the unloading is completed; S6. After a single loading-unloading task is completed, the vehicle returns from the unloading area to the road driving area. During the unloaded driving process in the road driving area, if a task completion command is received from the platform, the state switch is exited, the steering wheel is turned back to the center, and the vehicle speed gradually decreases to 0 until it stops; otherwise, the main state switch logic is followed and the operation continues.

6. The fully automated operation method for a cab-less mining dump truck according to claim 5, characterized in that, In step S2, the vehicle travels in the road driving area in the forward direction without a load, with the unloading direction of the bucket being the rear of the vehicle and the other end being the front of the vehicle. When the front of the vehicle is in front, it is in the forward direction; when the rear of the vehicle is in front, it is in the reverse direction. The decision-making layer combines location and environmental information to determine the main state as a road driving zone. The planning layer generates a data acquisition path that satisfies the motion constraints of a driverless vehicle based on the main state of the road driving zone determined by the decision-making layer. The control layer updates the vehicle parameters and performs tracking control based on the path and location information from the planning layer. At the same time, it calculates the distance to the boundary in real time and switches the corresponding state based on obstacle detection information.

7. The fully automated operation method for a cab-less mining dump truck according to claim 6, characterized in that, Step S3 includes the following sub-steps: S31, the decision-making level determines whether to enter the loading pre-stop position from the road driving area. If the determination is yes, drive forward into the loading pre-stop position. After entering the loading pre-stop position, determine whether it is allowed to enter the loading point. If yes, continue to execute; otherwise, continue to wait. S32, the planning layer plans the path from the pre-loading dock to the loading point based on the specified loading point, and sends it to the control layer to control the vehicle to reach the loading point; S33, after loading is completed, the planning layer plans the exit path from the loading point in reverse and sends it to the control layer; S34, the control layer receives the departure planning information, processes the location information and departure command, tracks the vehicle, and leaves the loading area; S35, in the main loading zone state, when an obstacle is detected, it will directly avoid the obstacle and stop without judging whether to detour, until no more obstacles are detected, and then switch to normal driving. Additionally, if the distance between the vehicle and the road boundary is less than a safety threshold, the vehicle will attempt to avoid obstacles and stop.

8. The fully automated operation method for a cab-less mining dump truck according to claim 7, characterized in that, In step S4, the vehicle travels in the opposite direction with a full load in the road driving area; the decision layer determines the main state as the road driving area by combining the location information and environmental information; the planning layer generates a collection path that meets the motion constraints of the driverless vehicle based on the main state of the road driving area determined by the decision layer; the control layer updates the vehicle parameters and performs tracking control based on the path and location information of the planning layer, while calculating the distance to the boundary in real time and switching the corresponding state based on the obstacle detection information.

9. A fully automated operation method for a cab-less mining dump truck according to claim 8, characterized in that, Step S5 includes the following sub-steps: S51, the decision-making level determines whether to enter the unloading pre-stop position from the road driving area. If the determination is yes, then drive in the opposite direction to enter the designated stop position; after entering the unloading area pre-stop position, determine whether it is allowed to enter the unloading point. If yes, continue to execute; otherwise, continue to wait. S52, the planning layer plans the driving route from the unloading pre-stop position to the designated unloading point based on the specified unloading point, and sends the driving route to the control layer for tracking and control to ensure the vehicle reaches the unloading point; S53, after unloading is completed, the planning layer plans the exit path from the unloading point in the forward direction and sends it to the control layer; S54, the control layer receives the planning information, and based on the location information and the planning layer path, it tracks and controls the vehicle to leave the unloading area; In the main state of the unloading zone, the S55 will directly avoid obstacles and stop when it detects an obstacle, without needing to determine whether to detour, until no more obstacles are detected, and then switch to normal driving. Additionally, if the distance between the vehicle and the road boundary is less than a safety threshold, the vehicle will attempt to avoid obstacles and stop.

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