Wheel-ground matching-based planetary vehicle path planning method and device

Abstract

The embodiment of the application discloses a star ball vehicle path planning method and device based on wheel-ground matching, and the method comprises the following steps: constructing a star ball vehicle single-wheel moving comprehensive cost map based on a digital elevation terrain map; performing global path planning of a star ball vehicle multi-wheel moving configuration on the star ball vehicle single-wheel moving comprehensive cost map to obtain a path point set; extracting a key point from the path point set, performing curve fitting based on the key point to obtain a moving path, calculating a whole vehicle moving cost for the moving path, adjusting the key point based on the whole vehicle moving cost to continuously optimize the moving path, and finally obtaining an optimal path. The application is helpful to improve the accuracy of star ball vehicle path planning.

Description

Technical Field

[0001] This invention relates to the fields of remote operation and movement path planning for planetary rovers, and more specifically, to a method and apparatus for planetary rover path planning based on wheel-to-ground matching. Background Technology

[0002] The planetary rover path planning method involves perceiving the surrounding terrain in an extraterrestrial environment using stereo vision or other depth sensors, generating a 3D terrain product, extracting multi-dimensional unstructured terrain attributes such as slope, aspect, and roughness based on depth information, and constructing a passable cost layer by combining the planetary rover's mobility performance and constraints. A global path search is then performed on the cost map to obtain a collision-free, low-cost, safe, and shortest path for the planetary rover, while also considering the planetary rover's kinematics to optimize trajectory smoothness.

[0003] Path planning is a crucial step in extraterrestrial rover exploration, and its movement in complex and dangerous environments poses significant safety risks. Current mainstream rover path planning algorithms simplify the rover into a point mass model. After identifying obstacles, the algorithms inflate these obstacles based on the rover's size, then search for path points within the point mass model. Finally, they use circular arc fitting to create a continuous and smooth path. However, with the advancement of lunar and interstellar exploration, and the increasing exploration of scientifically valuable extraterrestrial regions, the terrain and environments being explored are becoming increasingly complex. In areas with dense obstacles, path planning based on point mass inflation may fail to find an effective path, or even the optimal path for the rover. Summary of the Invention

[0004] In order to solve at least one of the technical problems in the background art, the present invention proposes a planetary rover path planning method and device based on wheel-ground matching.

[0005] To achieve the above objectives, according to one aspect of the present invention, a planetary rover path planning method based on wheel-ground matching is provided, the method comprising:

[0006] Constructing a comprehensive cost map of a planetary vehicle's single-wheel movement based on digital elevation topographic maps;

[0007] Global path planning for the multi-wheeled movement configuration of the planetary vehicle is performed on the single-wheeled movement comprehensive cost map to obtain the path point set;

[0008] Key points are extracted from the set of path points, and a movement path is obtained by curve fitting based on the key points. The movement cost of the whole vehicle is calculated for the movement path, and the key points are adjusted based on the movement cost of the whole vehicle to continuously optimize the movement path, and finally the optimal path is obtained.

[0009] Optionally, the construction of the comprehensive cost map for the single-wheel movement of the planetary vehicle based on the digital elevation topographic map specifically includes:

[0010] An evaluation window for each wheel of the planetary vehicle is constructed based on its dimensions.

[0011] The comprehensive cost value of each location on the digital elevation topographic map is calculated based on the evaluation window.

[0012] Based on the comprehensive cost, construct a comprehensive cost diagram for the single-wheel movement of the planetary vehicle.

[0013] Optionally, calculating the comprehensive cost value of each location on the digital elevation topographic map based on the evaluation window specifically includes:

[0014] The slope, roughness, and flatness at each location on the digital elevation topographic map are determined based on the evaluation window.

[0015] The comprehensive cost value of each location on the digital elevation topographic map is determined based on the slope, roughness, and flatness of each location.

[0016] Optionally, the step of performing global path planning for the multi-wheeled movement configuration of the planetary rover on the single-wheeled movement comprehensive cost map to obtain a path point set specifically includes:

[0017] When determining the next path point corresponding to the target path point, the rover's heading is calculated based on the target path point and its adjacent position points;

[0018] The position of each wheel of the planetary rover is determined based on the target waypoint and the heading.

[0019] Calculate the total cost of each wheel's position based on its individual position.

[0020] The adjacent position point with the smallest total cost of the wheel positions corresponding to the target path point is determined as the next path point corresponding to the target path point.

[0021] Optionally, extracting key points from the set of path points specifically includes:

[0022] Key points are extracted based on the turning angle between three consecutive path points in the path point set.

[0023] Optionally, the step of adjusting key points based on the vehicle movement cost to continuously optimize the movement path and ultimately obtain the optimal path specifically includes:

[0024] For each key point, after adjusting the key point to each adjacent grid point, curve fitting is performed to obtain a new movement path. The overall vehicle movement cost of the new movement path is calculated, and then the optimal adjacent grid point corresponding to each key point is determined based on the overall vehicle movement cost of the new movement path.

[0025] After adjusting each key point to its corresponding optimal adjacent grid point, curve fitting is performed to obtain the optimal movement path.

[0026] Optionally, calculating the vehicle movement cost for the movement path specifically includes:

[0027] The movement path is discretized to obtain discrete path points and the yaw angle corresponding to each discrete path point.

[0028] The position of each wheel of the planetary rover at each of the discrete path points is determined based on the yaw angle.

[0029] Based on the position of each wheel of the rover at each discrete path point and the comprehensive cost value of each position on the digital elevation topographic map, the comprehensive cost value corresponding to each discrete path point is determined.

[0030] Calculate the vehicle tilt angle and ground clearance of the planetary rover at each of the discrete path points;

[0031] The overall vehicle movement cost is determined based on the comprehensive cost value corresponding to each discrete path point, the vehicle tilt angle, and the ground clearance of the vehicle floor.

[0032] To achieve the above objectives, according to another aspect of the present invention, a planetary rover path planning device based on wheel-ground matching is provided, the device comprising:

[0033] A single-wheel movement comprehensive cost map construction unit is used to construct a planetary vehicle single-wheel movement comprehensive cost map based on a digital elevation topographic map.

[0034] A global path planning unit for multi-wheeled mobility configuration is used to perform global path planning for the multi-wheeled mobility configuration of the planetary vehicle on the single-wheeled mobility comprehensive cost map of the planetary vehicle, and obtain a set of path points;

[0035] The trajectory fitting and optimization unit is used to extract key points from the set of path points, perform curve fitting based on the key points to obtain a movement path, calculate the vehicle movement cost for the movement path, adjust the key points based on the vehicle movement cost to continuously optimize the movement path, and finally obtain the optimal path.

[0036] To achieve the above objectives, according to another aspect of the present invention, a computer device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described wheel-to-ground matching-based planetary rover path planning method.

[0037] To achieve the above objectives, according to another aspect of the present invention, a computer-readable storage medium is also provided, on which a computer program / instructions are stored, which, when executed by a processor, implement the steps of the above-described wheel-to-ground matching-based planetary rover path planning method.

[0038] The beneficial effects of this invention are as follows:

[0039] This invention first constructs a comprehensive cost map for the single-wheel movement of a planetary vehicle based on a digital elevation topographic map. Then, it performs global path planning for the multi-wheel movement configuration of the planetary vehicle on this comprehensive cost map to obtain a path point set. Key points are then extracted from this path point set, and curve fitting is performed based on these key points to obtain the movement path. The overall vehicle movement cost is calculated for this movement path, and the key points are adjusted based on the overall vehicle movement cost to continuously optimize the movement path, ultimately obtaining the optimal path. This invention performs a detailed analysis of the planetary vehicle's passable cost from three levels: single-wheel, multi-wheel, and overall vehicle, ultimately determining the optimal movement path, thereby improving the accuracy of planetary vehicle path planning. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0041] Figure 1 This is the first flowchart of the planetary rover path planning method based on wheel-to-ground matching in an embodiment of the present invention;

[0042] Figure 2 This is the second flowchart of the planetary rover path planning method based on wheel-to-ground matching in an embodiment of the present invention;

[0043] Figure 3 This is the third flowchart of the planetary rover path planning method based on wheel-to-ground matching in an embodiment of the present invention;

[0044] Figure 4 This is the fourth flowchart of the planetary rover path planning method based on wheel-to-ground matching in an embodiment of the present invention;

[0045] Figure 5This is the fifth flowchart of the planetary rover path planning method based on wheel-to-ground matching in this embodiment of the invention;

[0046] Figure 6 This is the sixth flowchart of the planetary rover path planning method based on wheel-to-ground matching in this embodiment of the invention;

[0047] Figure 7 This is an overall flowchart of the planetary rover path planning method according to an embodiment of the present invention;

[0048] Figure 8 This is the calculation process of the comprehensive cost map of planetary vehicle movement based on a single wheel, as described in this embodiment of the invention.

[0049] Figure 9 This is a schematic diagram illustrating the comprehensive cost calculation of the multi-round movement configuration in an embodiment of the present invention;

[0050] Figure 10 This is a schematic diagram of the method for extracting key points according to an embodiment of the present invention;

[0051] Figure 11 This is a schematic diagram of arc fitting according to an embodiment of the present invention;

[0052] Figure 12 This is a fitted path diagram showing the endpoint of an embodiment of the present invention that allows for turning in place;

[0053] Figure 13 This is a schematic diagram of the starting point in-situ turning plan in an embodiment of the present invention;

[0054] Figure 14 This is a schematic diagram of the vehicle trajectory comprehensive cost map calculation and trajectory optimization process according to an embodiment of the present invention;

[0055] Figure 15 This is a structural block diagram of the planetary rover path planning device based on wheel-to-ground matching according to an embodiment of the present invention;

[0056] Figure 16 This is a schematic diagram of a computer device according to an embodiment of the present invention. Detailed Implementation

[0057] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0058] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0059] It should be noted that the terms "comprising" and "having" and any variations thereof in the specification, claims and accompanying drawings of this invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such processes, methods, products or devices.

[0060] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0061] The technical problem this invention aims to solve is to implement a planetary rover movement path planning method and device based on wheel-ground matching, addressing the issue of excessively large obstacle expansion regions and mismatches with actual wheel trajectories in previous movement path planning methods using mass models, such as the inability to search for paths for the vehicle to cross obstacles. It establishes a refined path planning method based on the comprehensive cost of a multi-wheel model of the planetary rover. It also addresses the problem that the slope, roughness, and flatness of a single grid are insufficient to accurately assess the interaction between the vehicle and the actual terrain, calculating the actual wheel-ground contact area to evaluate vehicle tilt and ground clearance. Furthermore, it addresses the issue that previous local mass movement paths did not optimize for the actual wheel movement trajectory cost, establishing a comprehensive cost optimization method for wheel trajectories such as curvature walking and in-situ turning, achieving accurate path planning based on the true wheel movement trajectory.

[0062] Figure 7 This is an overall flowchart of the planetary rover path planning method according to an embodiment of the present invention, as follows: Figure 7As shown, the technical solution of this invention generally includes: path planning considering the movement configuration of the planetary rover and the mutual matching of wheels and ground, constructing a movement traversability cost calculation model of single-wheel-multi-wheel movement mechanism-whole vehicle, and performing a detailed analysis of the planetary rover's traversability cost, instead of treating it as a point mass model. Specifically, it establishes a single-wheel grid based on wheel-ground contact to calculate roughness, flatness, and slope, and analyzes the single-wheel movement cost; during global path search, it calculates the path cost of multi-wheel soil contact areas based on different yaws of the vehicle body, and searches for the optimal movement path point; finally, during local trajectory curve fitting and minimum cost optimization, it calculates the vehicle body tilt, wheel safety, and maximum gap between the vehicle floor and the ground based on the current movement form of the vehicle body, weights these to form the whole vehicle wheel movement trajectory cost, performs key point position adjustment, curve fitting, cost calculation, movement trajectory optimization, and iteratively outputs the movement trajectory.

[0063] The planetary rover path planning method based on wheel-ground matching specifically refers to: 1) calculating the environmental costs of roughness, flatness, and slope based on a single-wheel grid during the environmental modeling stage; 2) calculating the costs of multi-wheel movement patterns on the single-wheel passable cost map and globally searching for the optimal set of path points; 3) in the local optimization stage, extracting key points from the path point set based on motion constraint rules, fitting path curves within the area constrained by the key points, calculating the comprehensive costs of basic movement modes such as curvature motion, linear motion, and turning in place, and simultaneously incorporating the cost functions of vehicle tilt and the maximum gap between the chassis and the ground for final trajectory iterative optimization.

[0064] Figure 1 This is the first flowchart of the planetary rover path planning method based on wheel-to-ground matching according to an embodiment of the present invention, as follows: Figure 1 As shown, in one embodiment of the present invention, the planetary rover path planning method based on wheel-ground matching of the present invention includes steps S101 to S103.

[0065] Step S101: Construct a comprehensive cost map of the planetary vehicle's single-wheel movement based on the digital elevation topographic map.

[0066] Step S102: Perform global path planning for the multi-wheeled movement configuration of the planetary vehicle on the single-wheeled movement comprehensive cost map of the planetary vehicle to obtain the path point set.

[0067] Step S103: Extract key points from the path point set, perform curve fitting based on the key points to obtain the movement path, calculate the vehicle movement cost for the movement path, adjust the key points based on the vehicle movement cost to continuously optimize the movement path, and finally obtain the optimal path.

[0068] like Figure 2As shown, in one embodiment of the present invention, the above step S101 of constructing a comprehensive cost map of the single-wheel movement of the planetary vehicle based on a digital elevation topographic map specifically includes steps S201 to S203.

[0069] Step S201: Construct an evaluation window for the planet car's single wheel based on its dimensions.

[0070] In one embodiment of the present invention, the present invention constructs an evaluation window based on the maximum envelope side length d of the wheel. The maximum envelope side length d refers to the diagonal length of the top view of a single wheel, which is used to simplify the rotation of the wheel. When the position where the center of a single wheel contacts the ground is (xi, yj), a square area with (xi, yj) as the center and d as the side length is used as the evaluation window.

[0071] Step S202: Calculate the comprehensive cost value of each location on the digital elevation topographic map based on the evaluation window.

[0072] In one embodiment of the present invention, an evaluation window is set at each location on the digital elevation topographic map, and then the comprehensive cost value of each location on the digital elevation topographic map is calculated based on the evaluation window.

[0073] In one embodiment of the present invention, the digital elevation topographic map is specifically a raster map, and the size of the raster can be freely set according to the degree of refinement. The position in this step refers to each raster point in the digital elevation topographic map.

[0074] Step S203: Construct a comprehensive cost map for the single-wheel movement of the planetary vehicle based on the comprehensive cost value.

[0075] like Figure 3 As shown, in one embodiment of the present invention, the above step S202, which calculates the comprehensive cost value of each location on the digital elevation topographic map according to the evaluation window, specifically includes steps S301 and S302.

[0076] Step S301: Determine the slope, roughness, and flatness of each location on the digital elevation topographic map according to the evaluation window.

[0077] Step S302: Determine the comprehensive cost value of each location in the digital elevation topographic map based on the slope, roughness, and flatness of each location.

[0078] To achieve path planning based on wheel matching, this invention focuses on establishing a global path search and local trajectory optimization method for a planetary rover based on wheel movement trajectories. Refined path planning is achieved by optimizing the motion cost of the wheel-to-ground contact area along the rover's movement path. The terrain can be calculated using a binocular camera vision system to obtain a digital elevation evaluation map (DEM). The wheel-to-ground contact area is calculated based on the rover's movement configuration. Taking a multi-wheeled rover as an example, the rover's configuration can be represented as (x, y, theta), where x and y are the vehicle's positions, and theta is the vehicle's heading. The position (xi, yj) of the i-th wheel is calculated under the (x, y, theta) configuration. A square centered at (xi, yj) with a wheel scale d as its side length is used as the evaluation window for a single wheel to calculate the movement cost. The wheel movement cost at different positions is calculated under the constraints of the planetary configuration.

[0079] This invention acquires a Digital Elevation Map (DEM) using a camera on a planetary rover, and constructs a comprehensive cost map of movement based on a single wheel as a point mass model. Generally, the terrain resolution 'a' of the DEM is much smaller than the maximum envelope side length 'd' of a single wheel. The maximum envelope side length 'd' refers to the diagonal length of the top view of a single wheel, used to simplify wheel rotation. When the center of the single wheel contacts the ground at position (xi, yj), a square region centered at (xi, yj) with side length 'd' is used as the evaluation window. Within this window, quantitative indicators such as slope (slop), roughness, and flatness at the wheel's position (xi, yj) are calculated. Simultaneously, the maximum slope and roughness are set according to the constraints of movement performance, resulting in a comprehensive cost calculation method for a single wheel region. The wheel's slope is fitted to a plane based on the elevation values ​​within the evaluation window; the slope of this plane is the slop cost. The average distance from each point within the evaluation window to the plane is defined as flatness. The sum of the distances from the two points farthest from the plane on either side of the fitted plane within the evaluation window is the roughness. Normalization is performed based on the constraints of maximum slope, maximum roughness, and flatness. The cost of exceeding the constraints is set to 1, which is defined as an obstacle.

[0080] Figure 8 Taking four wheels as an example, this paper demonstrates the cost map calculation method based on a single wheel as a mass point model. The cost map of the wheel center point is calculated using the square of the maximum envelope of the wheel as the evaluation window. The cost map mainly includes slope, flatness, and roughness. The moving comprehensive cost map is obtained by combining the slope, flatness, and roughness evaluation indicators with different weights.

[0081] like Figure 4As shown, in one embodiment of the present invention, step S102 above involves global path planning of the planetary vehicle's multi-wheeled movement configuration on the single-wheeled movement comprehensive cost map of the planetary vehicle to obtain a path point set, specifically including steps S401 to S404.

[0082] Step S401: When determining the next path point corresponding to the target path point, calculate the rover's heading based on the target path point and its adjacent position points.

[0083] Step S402: Determine the position of each wheel of the planetary rover based on the target waypoint and the heading.

[0084] Step S403: Calculate the total comprehensive cost of each wheel position based on its individual position.

[0085] Step S404: The adjacent position point with the smallest total comprehensive cost of the wheel positions corresponding to the target path point is determined as the next path point corresponding to the target path point.

[0086] like Figure 7 As shown, after constructing the comprehensive cost map of a single-wheel movement, this invention performs a global search for the comprehensive cost of movement based on a multi-wheel configuration to obtain the optimal path set. The specific steps roughly include: reading the starting point or ending point; calculating adjacent positions; calculating the heading based on two adjacent positions; determining the position of each wheel at the specified position and heading; summing the single-wheel costs for all wheel positions; selecting the next path point with the minimum cost; and iteratively searching for the optimal path point set from the starting point to the ending point.

[0087] Specifically, in the global path search phase, the planetary vehicle is modeled as a multi-wheeled movement model. The multi-wheeled comprehensive cost of the vehicle's configuration is calculated on the comprehensive cost map constructed from a single wheel. A collision-free movement path is then searched using a global path search method. The cost function is:

[0088]

[0089] Where (i, j) represents the rover's position, θ is the rover's yaw angle, n is the number of wheels, and g(i, j) is the environmental cost function for grid point (i, j) in step one. The method for calculating the position of a single wheel in the (i, j, θ) configuration can be obtained through matrix rotation. When n = 4, the positions of the four wheels can be calculated as follows:

[0090]

[0091] This invention can employ path search algorithms based on Field D* or A* to search for optimal path points. In the path planning algorithm based on the planetary rover configuration of this invention, the search cost function is defined as:

[0092] f(s) = g(s) + h(s)

[0093]

[0094]

[0095] Where f(s) represents the estimated cost of traveling from the starting point to the destination via point s, g(s) is the actual cost of traveling from point s to the destination, h(s) is the heuristic function representing the estimated cost from the starting point to point s, defined as the Euclidean distance from the starting point to point s. i The vehicle movement cost and distance cost l(s,s) under the current configuration i The sum of ) and the yaw angle of the vehicle configuration is defined as s to s i direction

[0096] This invention can obtain the set of path points with minimum f(s) through a global path point search, such as... Figure 9 The path point set in the diagram, with the squares representing the wheel positions.

[0097] like Figure 7 As shown, after obtaining the path point set through global path point search, the present invention also performs local trajectory optimization based on minimizing the overall vehicle movement cost, specifically including two steps: trajectory fitting and local optimization.

[0098] The trajectory fitting steps specifically include: extracting key points based on the turning angle between three points in the path; fitting a circular arc curve based on the key points; discretizing the path at fixed distances to obtain a path point set, and calculating the movement cost and safety of the multi-wheel configuration; calculating the vehicle tilt angle, ground clearance, and safety under whole-wheel-ground matching, and normalizing them into matching cost; calculating the cost of the movement trajectory after weighting, and outputting the cost-optimal path.

[0099] The local optimization steps specifically include: reading key points; moving key point i to adjacent grid cells, curve fitting, cost calculation, and obtaining the optimal movement direction; determining the optimal movement direction and optimized cost value for all key points; comparing and optimizing the key point with the greatest impact on movement cost among all key points, updating the key points, and outputting the optimal path; iterating the above optimization process until the path is optimal.

[0100] In one embodiment of the present invention, the local trajectory optimization based on minimizing the overall vehicle movement cost is mainly divided into three steps. The first step is to extract key points from the path point set. The second step is to calculate the overall vehicle movement cost based on the curve fitting of the key points and the fitted curve, which mainly includes the cost under multi-wheel configuration, the vehicle tilt degree, and the weighted cost of ground clearance. The third step is trajectory optimization, which sets an optimization region in the key point area, adjusts the position of the key points, performs curve fitting and cost calculation, iterates the adjustment of position, curve fitting, and cost calculation process, and outputs the optimal motion trajectory.

[0101] In one embodiment of the present invention, the step S103 above, which involves extracting key points from the set of path points, specifically includes:

[0102] Key points are extracted based on the turning angle between three consecutive path points in the path point set.

[0103] In this invention, a set of path points is obtained during global path planning. For local optimization, key points are extracted for curve fitting, ultimately generating the rover's movement control parameters. Key point extraction primarily considers the kinematic constraints of the rover's minimum turning radius, ensuring that the curvature of the motion is achievable during movement or avoiding the special case of short-distance curvature motion where a straight line between two points is achievable.

[0104] Figure 10 This is a schematic diagram of the method for extracting key points according to an embodiment of the present invention, as shown below. Figure 10 As shown, in one embodiment of the present invention, the method for extracting key points specifically includes: adding the starting point to the key point set and setting the starting point as the path calculation endpoint; reading the path endpoint; reading the next path point; determining whether the endpoint and the current point are directly reachable; if so, reading the next path point; if not, adding it to the key point queue; determining whether the path point is the endpoint; if so, ending the process; if not, using the current point as the path endpoint and then reading the next path point.

[0105] like Figure 10 As shown, in another embodiment of the present invention, the method for extracting key points specifically includes: reading all path points and setting an initial value angle0 = 180°; reading the first two path points; reading the next point; calculating the included angle formed by the three points; recording the smaller included angle and the intermediate path point forming the smallest included angle; determining whether the path point is the endpoint, if so, deleting the intermediate point of the current smallest included angle, if not, reading the next point; determining whether the number of path points meets the set value, if so, ending, if not, proceeding to the step of reading all path points and setting an initial value angle0 = 180°.

[0106] In this invention, the movement path is obtained by curve fitting based on key points. After extracting the key points, path fitting is performed, and movement control parameters are output. Circular arcs are used to fit the curves between key points. The circular arcs between key points are calculated based on the starting point, ending point, and heading set by the vehicle body. The calculation method performs curve fitting separately according to whether the starting point and ending point support turning in place, and selects different path trajectories with the best results.

[0107] (1) Turning in place is not allowed at the starting point. Starting from the starting point, calculate the curvature of the circle based on the position of the previous point and its heading, and the position of the next point. That is, given the coordinates of two points on the circle and the tangent at one of the points, solve for the radius of the circle. Figure 11 As shown, let the heading angle of the AD tangent be ψ. The curvature 1 / R can be easily obtained according to the following calculation formula. If the curvature is less than a certain threshold, a straight line fitting is used. Then, the safety of the movement is calculated based on the multi-round comprehensive cost to ensure the passability of the path. The movement curvature and mileage of each path are obtained by fitting each key point in turn. Finally, the turning angle of the origin at the destination is determined according to the heading of the destination, so as to obtain the movement control parameters from the starting point to the destination.

[0108]

[0109]

[0110] (2) If turning in place is not allowed at the end point, the calculation is started from the end point, and the course of the end point is used as a constraint. The circular arc is fitted to the starting point in sequence, and the turning in place is achieved at the starting point.

[0111] (3) If there is no in-place turning constraint at the starting point and the ending point, the 360° is traversed at a specified interval, and the circular arc is fitted according to the method in (1) to obtain a series of control parameters under different flight directions, and at the same time, the optimal movement trajectory with the best comprehensive cost is given. Figure 12 The fitted path diagram that allows for in-place turns at the endpoint. Figure 13 This is a schematic diagram of a plan for turning in place from the starting point.

[0112] like Figure 5 As shown, in one embodiment of the present invention, the step S103 above, which adjusts key points based on the vehicle movement cost to continuously optimize the movement path and finally obtains the optimal path, specifically includes steps S501 and S502.

[0113] Step S501: For each key point, adjust the key point to each adjacent grid point and then perform curve fitting to obtain a new movement path. Calculate the vehicle movement cost of the new movement path, and then determine the optimal adjacent grid point corresponding to each key point based on the vehicle movement cost of the new movement path.

[0114] Step S502: After adjusting each key point to its corresponding optimal adjacent grid point, curve fitting is performed to obtain the optimal movement path.

[0115] After extracting key points and fitting the path, it is necessary to calculate the cost and optimize the fitted trajectory.

[0116] In one embodiment of the present invention, trajectory optimization is described below. Figure 14 The right-hand flow optimizes the key points of the path. After adjusting the position of the key points by a small fixed step size, the curve is refitted. All key points are traversed to find the key point with the greatest impact cost and its offset direction. This key point is adjusted. In each round of optimization, only one key point is moved by one step size. The iterative adjustment process continues until the optimal path is reached.

[0117] like Figure 7 As shown, the local optimization steps of the present invention specifically include: reading key points; moving key point i to adjacent grids, curve fitting, cost calculation, and obtaining the optimal movement direction; determining the optimal movement direction and the optimized cost value of all key points; comparing and optimizing the key point with the greatest impact on the movement cost among all key points, updating the key points, and outputting the optimal path; iterating the above optimization process until the path is optimal.

[0118] like Figure 6 As shown, in one embodiment of the present invention, the calculation of the vehicle movement cost for the movement path in step S103 specifically includes steps S601 to S605.

[0119] Step S601: Discretize the movement path to obtain discrete path points and the yaw angle corresponding to each discrete path point.

[0120] Step S602: Determine the position of each wheel of the planetary rover at each of the discrete path points based on the yaw angle.

[0121] Step S603: Determine the comprehensive cost value corresponding to each of the discrete path points based on the position of each wheel of the planetary rover at each of the discrete path points and the comprehensive cost value of each position on the digital elevation topographic map.

[0122] Step S604: Calculate the vehicle tilt angle and ground clearance of the vehicle floor at each of the discrete path points.

[0123] Step S605: Determine the overall vehicle movement cost based on the comprehensive cost value, vehicle tilt angle, and ground clearance of each discrete path point.

[0124] In one embodiment of the present invention, the calculation of the vehicle movement cost is as follows: Figure 14The left-hand flow reads trajectory parameters and discretizes the trajectory lines for various movement types, such as in-situ turns, curvature movements, and straight-line movements. A fixed distance is used for trajectory discretization. Based on the discretized trajectory points and corresponding headings, the comprehensive movement cost of the multi-wheeled planetary rover is calculated. The vehicle's tilt angle can be calculated based on the actual vehicle's movement subsystem structure or directly using surface fitting based on the average elevation values ​​of multiple wheel areas. The vehicle's ground clearance is calculated by obtaining the plane of the vehicle's undercarriage based on the tilt angle and then calculating the minimum distance from the undercarriage plane in the region below the vehicle.

[0125] like Figure 7 As shown, the specific steps for calculating the vehicle movement cost of the present invention include: obtaining a set of path points by discretizing the movement path at a fixed distance, calculating the movement cost and safety of the multi-wheel configuration; calculating the vehicle body tilt angle, ground clearance and safety under the whole vehicle wheel-ground matching, and normalizing them into matching cost; calculating the cost of the movement trajectory after weighting, and outputting the cost-optimal path.

[0126] As can be seen from the above embodiments, this invention solves the problem of fine path planning for wheeled mobile robots based on wheel-ground matching in complex environments. It achieves fine environment modeling under multi-level movement costs (single wheel, multi-wheel, and whole vehicle), and establishes a global path search based on wheel-ground matching cost calculation and a local trajectory optimization based on the proximity of key points. By selecting movement path points through global optimization of wheel-ground matching, the optimal movement path is determined. Key path points are extracted, and local optimization regions are set at these points to achieve iterative optimization of the local path, determining a better movement trajectory, thus realizing fine path planning based on wheel matching. The use of actual wheel movement trajectories for cost calculation effectively improves the solution space for movement path search in complex terrain. The establishment of multi-level cost calculation provides fine movement optimization, improving the effectiveness and precision of the movement path, and has high engineering application value.

[0127] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0128] Based on the same inventive concept, embodiments of the present invention also provide a planetary rover path planning device based on wheel-ground matching, which can be used to implement the planetary rover path planning method based on wheel-ground matching described in the above embodiments, as described in the following embodiments. Since the principle of the planetary rover path planning device based on wheel-ground matching is similar to that of the planetary rover path planning method based on wheel-ground matching, embodiments of the planetary rover path planning device based on wheel-ground matching can refer to embodiments of the planetary rover path planning method based on wheel-ground matching, and repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0129] Figure 15 This is a structural block diagram of the planetary rover path planning device based on wheel-to-ground matching according to an embodiment of the present invention, as shown below. Figure 15 As shown, in one embodiment of the present invention, the planetary rover path planning device based on wheel-to-ground matching of the present invention includes:

[0130] Single-wheel movement comprehensive cost map construction unit 1 is used to construct a single-wheel movement comprehensive cost map of the planetary vehicle based on a digital elevation topographic map;

[0131] The multi-wheeled mobility configuration global path planning unit 2 is used to perform global path planning for the multi-wheeled mobility configuration of the planetary vehicle on the single-wheeled mobility comprehensive cost map of the planetary vehicle, and obtain the path point set;

[0132] The trajectory fitting and optimization unit 3 is used to extract key points from the set of path points, perform curve fitting based on the key points to obtain a movement path, calculate the vehicle movement cost for the movement path, adjust the key points based on the vehicle movement cost to continuously optimize the movement path, and finally obtain the optimal path.

[0133] In one embodiment of the present invention, the single-round movement comprehensive cost graph construction unit 1 specifically includes:

[0134] The evaluation window construction module is used to construct an evaluation window for a single wheel of the planetary rover based on its size.

[0135] The comprehensive cost value calculation module is used to calculate the comprehensive cost value of each location on the digital elevation topographic map based on the evaluation window.

[0136] The mobile comprehensive cost map generation module is used to construct a single-wheel mobile comprehensive cost map of the planetary vehicle based on the comprehensive cost value.

[0137] In one embodiment of the present invention, the comprehensive cost calculation module specifically includes:

[0138] The index calculation submodule is used to determine the slope, roughness, and flatness of each location on the digital elevation topographic map based on the evaluation window.

[0139] The index comprehensive calculation submodule is used to determine the comprehensive value of each location in the digital elevation topographic map based on the slope, roughness, and flatness of each location.

[0140] In one embodiment of the present invention, the multi-round movement configuration global path planning unit 2 specifically includes:

[0141] The heading calculation module is used to calculate the heading of the rover based on the target path point and its adjacent position points when determining the next path point corresponding to the target path point.

[0142] A wheel position determination module is used to determine the position of each wheel of the planetary rover based on the target path point and the heading.

[0143] The comprehensive cost value calculation module is used to calculate the comprehensive cost value of each wheel position based on its individual position.

[0144] The path point determination module is used to determine the adjacent position point with the smallest total comprehensive cost of the wheel positions corresponding to the target path point as the next path point corresponding to the target path point.

[0145] In one embodiment of the present invention, the trajectory fitting and optimization unit 3 specifically includes:

[0146] The key point extraction module is used to extract key points based on the turning angle between three consecutive path points in the path point set.

[0147] In one embodiment of the present invention, the trajectory fitting and optimization unit 3 specifically includes:

[0148] The key point adjustment module is used to adjust each key point to each adjacent grid point, perform curve fitting to obtain a new movement path, calculate the vehicle movement cost of the new movement path, and then determine the optimal adjacent grid point corresponding to each key point based on the vehicle movement cost of the new movement path.

[0149] The optimal movement path determination module is used to adjust each of the key points to their respective optimal adjacent grid points and then perform curve fitting to obtain the optimal movement path.

[0150] In one embodiment of the present invention, the trajectory fitting and optimization unit 3 specifically includes:

[0151] The movement path discretization module is used to discretize the movement path to obtain discrete path points and the yaw angle corresponding to each discrete path point.

[0152] A discrete path point wheel position determination module is used to determine the position of each wheel of the planetary rover at each discrete path point based on the yaw angle.

[0153] The discrete path point comprehensive cost calculation module is used to determine the comprehensive cost value corresponding to each discrete path point based on the position of each wheel of the planetary rover at each discrete path point and the comprehensive cost value of each position on the digital elevation topographic map.

[0154] The discrete path point evaluation parameter calculation module is used to calculate the vehicle tilt angle and ground clearance of the vehicle floor at each of the discrete path points.

[0155] The vehicle movement cost determination module is used to determine the vehicle movement cost based on the comprehensive cost corresponding to each discrete path point, the vehicle tilt angle, and the ground clearance of the vehicle floor.

[0156] To achieve the above objectives, according to another aspect of this application, a computer device is also provided. For example... Figure 16 As shown, the computer device includes a memory, a processor, a communication interface, and a communication bus. The memory stores a computer program that can run on the processor. When the processor executes the computer program, it implements the steps in the method of the above embodiments.

[0157] The processor can be a central processing unit (CPU). The processor can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations of the above types of chips.

[0158] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and units, such as the program units corresponding to the above-described method embodiments of the present invention. The processor executes various functional applications and data processing of the processor by running the non-transitory software programs, instructions, and modules stored in the memory, thereby implementing the methods described in the above-described method embodiments.

[0159] The memory may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created by the processor, etc. Furthermore, the memory may include high-speed random access memory and non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include memory remotely located relative to the processor, which can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0160] The one or more units are stored in the memory and, when executed by the processor, perform the methods described in the above embodiments.

[0161] The specific details of the aforementioned computer equipment can be understood by referring to the relevant descriptions and effects in the above embodiments, and will not be repeated here.

[0162] To achieve the above objectives, according to another aspect of this application, a computer-readable storage medium is also provided, which stores a computer program that, when executed in a computer processor, implements the steps in the above-described wheel-to-ground matching-based planetary rover path planning method. Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium may also include combinations of the above types of memory.

[0163] To achieve the above objectives, according to another aspect of this application, a computer program product is also provided, including a computer program / instructions that, when executed by a processor, implement the steps of the above-described wheel-to-ground matching-based planetary rover path planning method.

[0164] Obviously, those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device, or fabricating them separately as individual integrated circuit modules, or fabricating multiple modules or steps as a single integrated circuit module. Thus, the present invention is not limited to any particular hardware and software combination.

[0165] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A wheel-matching-based planetary vehicle path planning method, characterized in that, include: Constructing a comprehensive cost map of a planetary vehicle's single-wheel movement based on digital elevation topographic maps; Global path planning for the multi-wheeled movement configuration of the planetary vehicle is performed on the single-wheeled movement comprehensive cost map to obtain the path point set; Key points are extracted from the set of path points, and a circular arc curve is fitted based on the key points to obtain the movement path. The movement cost of the whole vehicle is calculated for the movement path, and the key points are adjusted based on the movement cost of the whole vehicle to continuously optimize the movement path, and finally the optimal path is obtained. The construction of the comprehensive cost map for the single-wheel movement of the planetary rover based on digital elevation topographic maps specifically includes: An evaluation window for each wheel of the planetary vehicle is constructed based on its dimensions. The comprehensive cost value of each location on the digital elevation topographic map is calculated based on the evaluation window. Construct a comprehensive cost diagram for the single-wheel movement of the planetary vehicle based on the comprehensive cost value described above; The calculation of the comprehensive cost value of each location on the digital elevation topographic map based on the evaluation window specifically includes: The slope, roughness, and flatness at each location on the digital elevation topographic map are determined based on the evaluation window. The comprehensive cost value of each location on the digital elevation topographic map is determined based on the slope, roughness, and flatness of each location. The extraction of key points from the set of path points specifically includes: Key points are extracted based on the turning angle between three consecutive path points in the path point set.

2. The wheel-maze-based planetary rover path planning method according to claim 1, wherein, The step of performing global path planning for the multi-wheeled movement configuration of the planetary vehicle on the single-wheeled movement comprehensive cost map to obtain a path point set specifically includes: When determining the next path point corresponding to the target path point, the rover's heading is calculated based on the target path point and its adjacent position points; The position of each wheel of the planetary rover is determined based on the target waypoint and the heading. Calculate the total cost of each wheel's position based on its individual position. The adjacent position point with the smallest total cost of the wheel positions corresponding to the target path point is determined as the next path point corresponding to the target path point.

3. The planetary rover path planning method based on wheel-ground matching according to claim 1, characterized in that, The process of continuously optimizing the movement path based on the key points of the vehicle movement cost to ultimately obtain the optimal path specifically includes: For each key point, after adjusting the key point to each adjacent grid point, curve fitting is performed to obtain a new movement path. The overall vehicle movement cost of the new movement path is calculated, and then the optimal adjacent grid point corresponding to each key point is determined based on the overall vehicle movement cost of the new movement path. After adjusting each key point to its corresponding optimal adjacent grid point, curve fitting is performed to obtain the optimal movement path.

4. The planetary rover path planning method based on wheel-ground matching according to claim 1, characterized in that, The calculation of the vehicle movement cost for the movement path specifically includes: The movement path is discretized to obtain discrete path points and the yaw angle corresponding to each discrete path point. The position of each wheel of the planetary rover at each of the discrete path points is determined based on the yaw angle. Based on the position of each wheel of the rover at each discrete path point and the comprehensive cost value of each position on the digital elevation topographic map, the comprehensive cost value corresponding to each discrete path point is determined. Calculate the vehicle tilt angle and ground clearance of the planetary rover at each of the discrete path points; The overall vehicle movement cost is determined based on the comprehensive cost value corresponding to each discrete path point, the vehicle tilt angle, and the ground clearance of the vehicle floor.

5. A planetary rover path planning device based on wheel-ground matching, characterized in that, include: A single-wheel movement comprehensive cost map construction unit is used to construct a planetary vehicle single-wheel movement comprehensive cost map based on a digital elevation topographic map. A global path planning unit for multi-wheeled mobility configuration is used to perform global path planning for the multi-wheeled mobility configuration of the planetary vehicle on the single-wheeled mobility comprehensive cost map of the planetary vehicle, and obtain a set of path points; The trajectory fitting and optimization unit is used to extract key points from the set of path points, perform arc curve fitting based on the key points to obtain the movement path, calculate the vehicle movement cost for the movement path, adjust the key points based on the vehicle movement cost to continuously optimize the movement path, and finally obtain the optimal path. The single-round movement comprehensive cost graph construction unit specifically includes: The evaluation window construction module is used to construct an evaluation window for a single wheel of the planetary rover based on its size. The comprehensive cost value calculation module is used to calculate the comprehensive cost value of each location on the digital elevation topographic map based on the evaluation window. The comprehensive cost map generation module is used to construct a single-wheel comprehensive cost map of the planetary vehicle's movement based on the comprehensive cost value. The comprehensive cost calculation module specifically includes: The index calculation submodule is used to determine the slope, roughness, and flatness of each location on the digital elevation topographic map based on the evaluation window. The index comprehensive calculation submodule is used to determine the comprehensive value of each location in the digital elevation topographic map based on the slope, roughness, and flatness of each location. The trajectory fitting and optimization unit specifically includes: The key point extraction module is used to extract key points based on the turning angle between three consecutive path points in the path point set.

6. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 4.

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