An extraterrestrial mission area search path planning method based on an elevation map

Abstract

The application discloses an extraterrestrial celestial body task area search path planning method based on an elevation map and belongs to the technical field of space robots. The method is as follows: the slope data in a task area is solved through the point set data of the elevation map, and the alternative passing position points of the rover are determined; the planning grid size is determined, and whether the grid is passable is determined according to the proportion of the number of passable points in the grid to the total number as a judgment standard; the exploration value of each grid is determined, and a weight value is assigned to the grid. The current grid is taken as a center point, the detectable nodes in a predetermined range around the current grid are marked as detected nodes, and the weight values of the detected nodes are reduced; the value of each grid in the passable range around the current grid is judged with the current grid as a center point, if there is a grid with a value not less than an end threshold, the grid with the maximum value is selected as a next path node, the above steps are repeated, and the extraterrestrial celestial body task area search path planning based on the elevation map is realized.

Description

Technical Field

[0001] This invention relates to a method for searching and planning a mission area for extraterrestrial objects based on an elevation map, and more particularly to a method for searching and planning a target of interest within a mission area when there are static, impassable areas on the lunar surface and the elevation map is known. This invention belongs to the field of space robotics technology. Background Technology

[0002] With the continuous development of aerospace technology, humans have the ability to send small rovers to extraterrestrial bodies. The rovers will search for targets of interest on their surfaces, effectively advancing related scientific research. During the search for targets of interest within the designated mission area, a path planning algorithm needs to be designed. However, due to the limitations of the extraterrestrial environment, more requirements are placed on the algorithm, mainly in the following aspects: (1) Since the distance between Earth and extraterrestrial bodies is far, remote operation will result in a large communication delay, so the rovers need to have autonomous planning capabilities and make autonomous decisions for path planning; (2) The surface of extraterrestrial bodies is often complex, with many impassable terrains such as craters and ravines. The above terrain may make the passable parts of the mission area irregular shapes, which makes it difficult to implement traditional spiral or grid search methods; (3) Due to design requirements such as radiation protection and reliability, the rovers will have a large computing power limitation. This makes the planning algorithm as simple and lightweight as possible, and the path planning module can be run online. In addition, since extraterrestrial missions often use orbiters to create digital elevation maps of the terrain in the early stages to select the most suitable mission area, this can provide prior elevation map information for the rover's mission planning.

[0003] There is currently little research on the search path planning technology for extraterrestrial mission areas, and the main research on the search path planning technology for mission areas is reflected in the field of ground mobile robots. The developed mission area search path planning technology [1] (see: Zhang Fangfang, Chen Bo, Ban Xuanxuan et al. Multi-robot cooperative search algorithm based on bio-inspired neural network and DMPC [J]. Control and Decision, 2021, 36(11):2699-2706.DOI:10.13195 / j.kzyjc.2020.0959.) studied a multi-robot cooperative search algorithm based on bio-inspired neural network and DMPC, which optimized the computational efficiency while ensuring obstacle avoidance. However, this method takes multi-robot cooperation as the research object and is not suitable for the search task of a single rovers.

[0004] Prior art [2] (see: Hao Kun, Deng Chaoshuo, Zhao Lu, et al. Robot path planning based on particle swarm algorithm for region search [J]. Journal of Electronic Measurement and Instrumentation, 2022, 36(12):126-135.DOI:10.13382 / j.jemi.B2205754.) studied the use of particle swarm algorithm for region search path planning, and proposed two variable operators to adjust the inertia weight factor and adaptively improve the acceleration factor to enhance the search ability of the algorithm at different times. The new acceleration factor is used to enable the particles to quickly get rid of the poor region. The disadvantage of this scheme is that although it improves the calculation speed of the traditional particle swarm algorithm, it is still difficult to meet the needs of online calculation. Summary of the Invention

[0005] The main objective of this invention is to provide a method for planning search paths for extraterrestrial mission areas based on elevation maps. The method transforms the search mission area into a grid map of passable areas based on elevation maps and rover maneuverability calculations. It also autonomously generates scanning search trajectories based on its own starting point and the exploration weight of the mission area, ensuring full coverage of passable areas. This method has advantages such as short computation time and reliable path planning.

[0006] The objective of this invention is achieved through the following technical solution:

[0007] This invention discloses a method for planning search paths in extraterrestrial mission areas based on elevation maps. It calculates regional slope data within the mission area using elevation map point set data, compares the maximum slope of each location point with the rover's off-road capability to determine alternative passable locations, determines the size of the planned grid based on the rover's size and turning ability, and uses the proportion of passable points within a grid to the total number of points as an evaluation criterion to determine whether a grid is passable, and determines the exploration value of each grid and assigns it a weight value. The exploration value types include unexplored areas, explored areas, impassable areas, and boundaries. Using the current grid cell as the center point, detectable nodes within a predetermined range are marked as detected nodes, and their weight values ​​are reduced. Using the current grid cell as the center point, the value of each grid cell within the traversable range is determined. If the value of all grid cells is less than the termination threshold, the task ends. If there are grid cells with a value not less than the termination threshold, the grid cell with the highest value is selected as the next path node. Starting from the next path node, the above steps are repeated until a path planning for extraterrestrial mission area search based on an elevation map is achieved.

[0008] This invention discloses a method for planning a search path for an extraterrestrial mission region based on an elevation map, comprising the following steps:

[0009] Step 1: Using the elevation map point set data, calculate the maximum slope data for each location point within the task area, and compare the maximum slope of each location point with the off-road capability of the patrol vehicle to determine the passable location points of the patrol vehicle.

[0010] If the height of the point in the i-th row and j-th column of the elevation map point set is H i,j Adding or subtracting 1 after i and after j respectively represents adding or subtracting a row and a column. Unless otherwise specified, all row and column transformations mentioned below follow this convention. The distance between two adjacent height sampling points is d0. The maximum slope S of each point on the elevation map is then calculated. i,j The expression is

[0011]

[0012] S i,j With the off-road capability of the patrol vehicle S max In comparison, the expression for the passability marker, used to determine whether each point on the elevation map is passable, is:

[0013]

[0014] Among them, s i,j >s max This indicates that the maximum gradient at this point exceeds the off-road capability of the patrol vehicle, classifying it as an impassable point, and is marked as 1; s i,j ≤s max This indicates that the maximum slope at this point is less than the off-road capability of the patrol vehicle, and it is a passable point, marked as 0.

[0015] Step 2: Determine the planned grid size d based on the size of the patrol device and its turning capability, and use the proportion of passable points within the grid to the total number n as the evaluation criterion to determine whether the grid is passable.

[0016] The number of height sampling points n contained in a single grid is

[0017]

[0018] The number of rows with a pass marker of 1 in the p-th row and q-th column of the raster is n. p,q If there are [number] grid cells, then the expression for whether the grid cell is passable is:

[0019]

[0020] Among them, T max n represents the maximum percentage of impassable points within a grid. p,q / n>T max This indicates that the grid has too many sampling points and does not meet the passability conditions, making it an impassable grid, marked as 1; n p,q / n≤T max This indicates that there are more sampling points within the grid that meet the passability conditions, and it is a passable grid, marked as 0;

[0021] Step 3: Assign a weight value to each grid cell based on the terrain features and task requirements.

[0022] Step 4: Using the grid where the rovers are currently located as the center point, mark the detectable nodes within the predetermined range around them as detected nodes.

[0023] If the weight value of the grid cell in row p and column q is w p,q The weight values ​​w of the detected grid have been obtained. done The rover is currently located in the a-th row and b-th column of the grid, with a detection radius of r. d Update the weight values ​​of all passable grid cells to 1.

[0024]

[0025] Step 5: Using the current grid cell of the rover as the center point, calculate the value of each grid cell within the passable area. If the value of all grid cells is less than the termination threshold or the passable area coverage has met the requirements, the mission ends. If the conditions are not met, select the grid cell with the highest value as the next path node, and then return to Step 4 from the next path node until the search path planning for the extraterrestrial object mission area based on the elevation map is achieved.

[0026] If the radius of the patrol vehicle's passable range is r t The sampling radius for calculating the value of each grid cell within the passable area is r. c The current grid cell where the patrol device is located is in row a and column b, and row m and column n are a certain grid cell within the passable area for this operation. m+x,n+y This represents the value of the raster cell in row (m+x) and column (n+y), where x and y are the changes in the row or column, respectively, and are integers.

[0027] The expression for the value of each grid cell within the current passable range is:

[0028]

[0029] Within the currently passable area, the grid with the highest value has the following weight:

[0030]

[0031] If the value of the grid with the highest value is less than the threshold, the task is terminated directly.

[0032] If the value of the grid with the highest value is greater than the threshold, then that grid is considered the next grid for the rovers to proceed to, and the process returns to step four until the mission ends and exits. The positions of each target grid obtained from the starting point are sequentially organized to obtain the complete search path within the mission area, thus completing the search path planning for this mission area.

[0033] It also includes step six: Based on the elevation map-based extraterrestrial mission area search path planning results obtained in step five, in actual lunar environment applications, combined with the node-to-node trajectory generation algorithm, the running path can be calculated more quickly and accurately, the target search task can be completed within the given mission area, and related engineering problems can be solved.

[0034] Beneficial effects:

[0035] 1. This invention discloses a method for searching and planning routes for extraterrestrial mission areas based on elevation maps. In determining the passable area grid, the slope of each location point is calculated using the elevation map and compared with the rover's off-road capability. Then, a reasonable threshold is used to distinguish and determine the passable grid. This two-layer judgment method provides more redundancy for the selection of passable grids, making the calculated passable areas more accurate and safer.

[0036] 2. This invention discloses a method for planning search paths for extraterrestrial mission areas based on elevation maps. By adding weight values, the method selects the node with the highest grid value within each passable area as the next node, thus sequentially determining and forming the search trajectory. This method autonomously calculates the search trajectory within the passable grid. Compared to directly generating a scanning trajectory according to a specific pattern, this method is more logical and has an advantage in ensuring coverage. Compared to traditional optimization methods for generating scanning trajectories, this method can significantly improve calculation speed, making it suitable for real-time calculation when the computing power of extraterrestrial rovers is low. Attached Figure Description

[0037] Figure 1 This invention discloses a schematic diagram of a method for regional search path planning for extraterrestrial missions based on elevation maps.

[0038] Figure 2 A digital elevation map of a certain area on the lunar surface in an example of this invention.

[0039] Figure 3 In this invention, the set of passable points is generated based on the slope.

[0040] Figure 4 In this invention, passable grid points are obtained through conversion.

[0041] Figure 5 The search trajectory designed in the example of this invention. Detailed Implementation

[0042] To better illustrate the purpose and advantages of this invention, the following example analysis of search path planning for a target of interest within a certain mission area on the lunar surface will provide a detailed explanation of this invention.

[0043] Example 1:

[0044] This example task involves planning a search path for a target of interest within a specific lunar surface region. With the increasing popularity of lunar exploration in recent years, more and more countries are launching rovers to the lunar surface for exploration missions. This example uses this as a background, envisioning a small rover measuring only 20cm*20cm*10cm to complete a special terrain exploration mission within a specific lunar surface region. The rover will conduct a coverage search within the mission area, looking for features such as small rocks and water flow traces. The mission area is located at the foot of a crater, measuring 12m*12m. The elevation map information for the mission area is provided by the orbiter satellite, with a sampling interval of 0.1m, and is considered known information. Due to the small size and high maneuverability of the rover (maximum off-road capability with a slope less than 0.75), a grid size of 0.4m*0.4m is selected, and the maximum percentage of impassable points within the grid is chosen to be 0.4. The probe has a detection radius of 4 grids, or 1.6m; a passable range of 5 grids, or 2m; a single sampling radius of 4 grids, or 1.6m; and a termination condition value threshold of 20.

[0045] like Figure 1 As shown in the figure, this embodiment discloses a method for planning a search path for an extraterrestrial mission region based on an elevation map. The specific implementation steps are as follows:

[0046] Step 1: Using the elevation map point set data, calculate the maximum slope data for each point within the task area, and compare the maximum slope of each location point with the off-road capability of the patrol vehicle to determine the passable location points of the patrol vehicle;

[0047] If the height of the point in the i-th row and j-th column of the elevation map point set is H i,j Adding or subtracting 1 after i and after j respectively represents adding or subtracting a row and a column. Unless otherwise specified, all row and column transformations mentioned below follow this convention. The distance between two adjacent height sampling points is d0. The maximum slope S of each point on the elevation map is then calculated. i,j The expression is

[0048]

[0049] S i,j With the off-road capability of the patrol vehicle S maxIn comparison, the expression for the passability marker, used to determine whether each point on the elevation map is passable, is:

[0050]

[0051] Among them, s i,j >s max This indicates that the maximum gradient at this point exceeds the off-road capability of the patrol vehicle, classifying it as an impassable point, and is marked as 1; s i,j ≤s max This indicates that the maximum slope at this point is less than the off-road capability of the patrol vehicle, and it is a passable point, marked as 0;

[0052] The visualization results of the task area elevation map are as follows: Figure 2 As shown, the passable area of ​​the task region, determined by the slope, is as follows: Figure 3 As shown in the diagram. Darker areas represent impassable areas, while lighter areas represent passable areas.

[0053] Step 2: Determine the planned grid size d based on the size of the patrol device and its turning capability, and use the proportion of passable points within the grid to the total number n as the evaluation criterion to determine whether the grid is passable.

[0054] The number of height sampling points n contained in a single grid is

[0055]

[0056] The number of rows with a pass marker of 1 in the p-th row and q-th column of the raster is n. p,q If there are [number] grid cells, then the expression for whether the grid cell is passable is:

[0057]

[0058] Among them, T max n represents the maximum percentage of impassable points within a grid. p,q / n>T max This indicates that the grid has too many sampling points and does not meet the passability conditions, making it an impassable grid, marked as 1; n p,q / n≤T max This indicates that there are more sampling points within the grid that meet the passability conditions, and it is a passable grid, marked as 0;

[0059] The calculation shows that the number of height sampling points contained in a single grid cell is 16. The resulting walkable grid diagram is shown below. Figure 4 As shown.

[0060] Step 3: Assign a weight value to each grid cell based on the terrain features and task requirements.

[0061] Considering the terrain features of this mission, including impassable areas and boundaries, a raster type was chosen for these. Furthermore, considering the mission requirement is to cover the entire exploration area, both unexplored and explored areas were also selected as raster types. The weights are defined in the table below.

[0062] Table 1 Grid Weight Settings

[0063]

[0064] In addition to encouraging the rover to move away from explored and impassable areas and into unexplored areas, the aforementioned weight settings also assign a large positive weight to the boundaries of the mission area. This ensures that the boundaries are searched during the trajectory design process, greatly reducing the possibility of missed searches.

[0065] Step 4: Using the grid where the rovers are currently located as the center point, mark all detectable nodes within a certain range around them as detected nodes;

[0066] If the weight value of the grid cell in row p and column q is w p,q The weight values ​​w of the detected grid have been obtained. done The rover is currently located in the a-th row and b-th column of the grid, with a detection radius of r. d Update the weight values ​​of all passable grid cells to 1.

[0067]

[0068] Step 5: Using the grid where the rovers are currently located as the center point, calculate the value of each grid within the passable area. If the value of all grids is less than the end threshold or the passable area coverage has met the requirements, the task ends. If the conditions are not met, select the grid with the highest value as the next path node, and then return to Step 4 with the next path node as the starting point.

[0069] If the radius of the patrol vehicle's passable range is r t The sampling radius for calculating the value of each grid cell within the passable area is r. c The current grid cell where the patrol device is located is in row a and column b, and row m and column n are a certain grid cell within the passable area for this operation. m+x,n+y This represents the value of the raster cell in row (m+x) and column (n+y), where x and y are the changes in the row or column, respectively, and are integers.

[0070] The expression for the value of each grid cell within the current passable range is:

[0071]

[0072] Within the currently passable area, the grid with the highest value has the following weight:

[0073]

[0074] If the value of the grid with the highest value is less than the threshold, the task is terminated directly.

[0075] If the value of the grid with the highest value is greater than the threshold, then that grid is considered the next grid for the rovers to proceed to, and the process returns to step four until the task ends and exits. The positions of each target grid obtained from the starting point are sequentially organized to obtain the complete search path within the task area, thus completing the task area search path planning task. The final generated result is as follows: Figure 5 As shown, in Figure 5 In the diagram, white represents passable areas, black represents impassable areas, and gray represents planned path nodes. The generated path nodes are labeled in chronological order and assigned sequential numbers; connecting the nodes in sequence forms the search trajectory. This method achieves 100% coverage of the passable areas in this example with a short computation time. Running this example on a computer with an Intel Core i7-9700F CPU at 3.00GHz, the time is only 0.16 seconds, significantly shorter than other optimized algorithms.

[0076] Step Six: Based on the elevation map-based extraterrestrial mission area search path planning results obtained in Step Five, in actual lunar environment applications, combined with node-to-node trajectory generation algorithms, the running path can be calculated more quickly and accurately, completing the target search task within the given mission area and solving related engineering problems.

[0077] The above detailed description further illustrates the purpose, technical solution, and beneficial effects of the invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. 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 method for planning search paths for extraterrestrial mission regions based on elevation maps, characterized in that: Includes the following steps, Step 1: Using the elevation map point set data, calculate the maximum slope data for each location point within the task area, and compare the maximum slope of each location point with the off-road capability of the patrol vehicle to determine the passable location points of the patrol vehicle; If the elevation map point set is the Line number The height of the column points is ,exist After +1 or -1 and in +1 or -1 indicates adding or subtracting a row and a column, respectively. Unless otherwise specified, all row and column transformations mentioned below will follow this expression method. The spacing between two adjacent height sampling points is... Then the maximum slope of each point on the elevation map can be calculated. The expression is Will Off-road capability of the patrol vehicle In comparison, the expression for the passability marker, used to determine whether each point on the elevation map is passable, is: in, This indicates that the maximum slope at this point exceeds the off-road capability of the patrol device, and it is considered an impassable point, marked as 1. This indicates that the maximum slope at this point is less than the off-road capability of the patrol vehicle, and it is a passable point, marked as 0; Step 2: Determine the planned grid size based on the size of the patrol vehicle and its turning capability. The passability of a grid is determined by the proportion of passable points within the grid to the total number of points. Number of height sampling points contained in a single grid for Statistics Line number The number of rows with a pass marker of 1 within a column grid is If there are [number] grid cells, then the expression for whether the grid cell is passable is: in, This represents the maximum percentage of impassable points within a grid cell. This indicates that the grid has too many sampling points and does not meet the passability conditions, so it is an impassable grid and is marked as 1. This indicates that there are more sampling points within the grid that meet the passability conditions, and it is a passable grid, marked as 0; Step 3: Assign a weight value to each grid cell based on the terrain features and task requirements; Step 4: Using the grid where the rovers are currently located as the center point, mark all detectable nodes within the predetermined range around them as detected nodes; If the first Line number The weight value of the column grid is The weight values ​​of the detected grid have been obtained. The current grid cell where the patrol device is located is the 1st grid cell. row and number The column has a detection radius of Update the weight values ​​of all passable grid cells to 1. Step 5: Using the current grid cell of the rover as the center point, calculate the value of each grid cell within the passable area. If the value of all grid cells is less than the termination threshold or the passable area coverage has met the requirements, the mission ends. If the conditions are not met, select the grid cell with the highest value as the next path node, and then return to Step 4 from the next path node until the search path planning for the extraterrestrial object mission area based on the elevation map is achieved.

2. The method for planning a search path for an extraterrestrial mission region based on an elevation map as described in claim 1, characterized in that: It also includes step six: Based on the elevation map-based extraterrestrial mission area search path planning results obtained in step five, in actual lunar environment applications, combined with the node-to-node trajectory generation algorithm, the running path can be calculated more quickly and accurately, the target search task can be completed within the given mission area, and related engineering problems can be solved.

3. A method for planning a search path for an extraterrestrial mission region based on an elevation map, as described in claim 1 or 2, characterized in that: Step five is implemented as follows: If the radius of the patrol's passable range is The sampling radius for calculating the value of each grid cell within the passable area is: The current grid cell where the patrol device is located is the 1st grid cell. row and number Column, number row and number Listed as a grid cell within the currently passable area; Indicates the first row and number The value of column grids These represent the changes in rows or columns, and are integers. The expression for the value of each grid cell within the current passable range is: Within the currently passable area, the grid with the highest value has the following weight: If the value of the grid with the highest value is less than the threshold, the task is terminated directly. If the value of the grid with the highest value is greater than the threshold, then the grid is regarded as the next grid for the rovers to move to, and the process returns to step four until the task ends and exits; the positions of each target grid obtained from the starting point are sorted in sequence to obtain the complete search path in the task area, thus completing the search path planning for this task area.

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