CN-120370928-B - Autonomous exploration method and device based on boundary and layering

CN120370928BCN 120370928 BCN120370928 BCN 120370928BCN-120370928-B

Abstract

The application discloses an autonomous exploration method and device based on boundary and layering, which relates to the field of autonomous exploration of robots, wherein the method comprises the steps of in a current two-dimensional grid map, A dynamic sliding window is arranged according to the current position of the robot, and the size of the sliding window can be regulated and controlled in a self-adaptive mode according to the uncertainty of the environment, the distribution of obstacles and the moving speed of the robot. In addition, the application selects one local target boundary point from the dynamic sliding window or selects one global target boundary point from each undetected global boundary point as a guide point, so that the RRT sampling algorithm plans a feasible path towards a designated direction, and the autonomous exploration efficiency is improved. In addition, the method selects the target boundary points, selects the target boundary points from the local boundary points or selects the target boundary points from the global boundary points, and layers the boundary points, so that the number of sampling points to be evaluated is reduced, and the autonomous exploration efficiency is improved.

Inventors

DENG HAOWEN
WANG HONGCHAO
RAO YUANSHENG
YIN JIABIN
MAO HUIYING

Assignees

重庆交通大学

Dates

Publication Date: 20260508
Application Date: 20250402

Claims (10)

1. An autonomous exploration method based on boundaries and layering, comprising: Acquiring environment information detected by a robot detection assembly and the current position of a robot; Constructing a two-dimensional grid map of a current detection area according to current environment information, and determining the state of each grid unit in the two-dimensional grid map, wherein the states of the grid units comprise an unknown area, an obstacle area and a free running area; Setting a dynamic sliding window according to the current position of the robot in the current two-dimensional grid map, wherein the size of the dynamic sliding window is determined according to the uncertainty of the environment, the distribution of obstacles and the movement speed of the robot; When a new boundary point is generated in the current dynamic sliding window, determining a target boundary point in each boundary point in the current dynamic sliding window, taking a non-target boundary point as a global boundary point, and deleting detected global boundary points in all current global boundary points, wherein the boundary points are grid units corresponding to a free running area bordering an unknown area; Using the target boundary point as a guide point, determining a feasible path from the current position of the robot to the target boundary point by using an RRT sampling algorithm to control the robot to move to the target boundary point according to the feasible path, and returning to the step of acquiring environment information detected by a robot detection component and the current position of the robot; When no new boundary point is generated in the current dynamic sliding window, selecting a target global boundary point from all the current undetected global boundary points, taking the target global boundary point as a target boundary point, returning to the step of using the target boundary point as a guide point, and determining a feasible path from the current position of the robot to the target boundary point by using an RRT sampling algorithm so as to control the robot to move to the target boundary point according to the feasible path.
2. The autonomous boundary and hierarchy based exploration method of claim 1, wherein determining the state of each grid cell in the two-dimensional grid map comprises: the logarithmic probability of each grid unit in the two-dimensional grid map is calculated, and the calculation formula of the logarithmic probability is as follows: Wherein z t refers to sensor observation data acquired by a laser radar and a depth camera sensor at a time t, l (m i,j ∣z 1:t ) is the logarithmic probability of a grid m i,j at the time t, l (m i,j ∣z 1:t-1 ) is the logarithmic probability of a grid at a time t-1, p (z t ∣m i,j =1) represents the likelihood probability that the sensor observes z t when the grid is occupied, and p (z t ∣m i,j =0) represents the likelihood probability that the sensor observes z t when the grid is idle; calculating the occupation probability of each grid unit according to the logarithmic probability, wherein the occupation probability has the expression: Wherein p (m i,j ) represents the occupancy probability of the grid cell; the state of each grid cell is divided according to the occupancy probability of each grid cell.
3. The autonomous boundary and hierarchy based exploration method of claim 2, wherein the partitioning of the state of each grid cell according to the occupancy probability of each grid cell comprises: If the occupancy probability of the grid unit is smaller than or equal to a first preset value, the corresponding grid unit is regarded as a free running area; If the occupancy probability of the grid unit is larger than or equal to a second preset value, the corresponding grid unit is regarded as an obstacle area; and if the occupancy probability of the grid unit is larger than the first preset value and smaller than the second preset value, the corresponding grid unit is regarded as an unknown area.
4. The autonomous exploration method based on boundaries and layering according to claim 2, characterized in that the dynamic sliding window is set according to the current position of the robot, comprising in particular: Determining an environmental dynamic factor of a current detection area according to the occupation probability of each grid unit in a two-dimensional grid map corresponding to the detection area of the current position of the robot; determining the density of the obstacle in the two-dimensional grid map corresponding to the detection area of the current position of the robot, and determining the complexity factor of the current detection area according to the density of the obstacle; Determining a speed factor of a current detection area according to the current movement speed of the robot; determining the size of a dynamic sliding window according to the environmental dynamic factor, the complexity factor and the speed factor; And setting the dynamic sliding window according to the size of the dynamic sliding window and the preset aspect ratio of the window.
5. The autonomous boundary and hierarchy based exploration method of claim 4, wherein a computational expression of a size of a dynamic sliding window is: ; Wherein N represents the size of the dynamic sliding window; Representing a preset base window size; representing an environmental dynamic factor; representing an information entropy value, wherein the information entropy value is determined according to the occupancy probability; Representing a complexity factor; Representing the obstacle density; Representing a speed factor; representing the speed of movement of the robot.
6. The autonomous exploration method based on boundaries and layering as claimed in claim 1, wherein the determining the target boundary point among the boundary points in the current dynamic sliding window comprises: Determining each boundary point in the current dynamic sliding window; Downsampling is carried out on all boundary points in the current dynamic sliding window, and boundary points after downsampling are obtained; Clustering the down-sampled boundary points, and regarding the boundary points in the same cluster as the same boundary point to obtain clustered boundary points; Dividing the surrounding environment of the robot into a plurality of subareas by taking the current position of the robot as the center; Selecting the clustered boundary points with the maximum gain as candidate boundary points for each subarea; The candidate boundary point of the maximum gain is selected from the sub-regions as the target boundary point.
7. The autonomous discovery method based on boundaries and layering of claim 1, wherein selecting a target global boundary point among all currently non-detected global boundary points specifically comprises: The access of all the current undetected global boundary points is completed in the shortest time as a target, and the access sequence of all the current undetected global boundary points is determined by utilizing a TSP algorithm; and taking the undetected global boundary point corresponding to the first access target in the access sequence as a target global boundary point.
8. A computer device comprising a memory, a processor and a computer program stored on the memory and running on the processor, characterized in that the processor executes the computer program to implement the boundary and hierarchy based autonomous exploration method of any of claims 1-7.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the boundary and hierarchy based autonomous exploration method of any of claims 1 to 7.
10. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the autonomous boundary-and hierarchy-based exploration method of any of claims 1 to 7.

Description

Autonomous exploration method and device based on boundary and layering Technical Field The application relates to the field of autonomous exploration of robots, in particular to an autonomous exploration method and device based on boundaries and layering. Background The field of autonomous exploration of robots is rapidly developed at present, and people develop and research on the autonomous exploration robots from various aspects of the robots, wherein the research is the most widely used autonomous exploration strategy of the robots, and a series of exploration strategies based on RRT algorithm takes an important role. The RRT algorithm is widely used for respective intelligent robots at present, and is mainly used for local path planning of autonomous movement of the intelligent robots, namely, a large number of random trees are rapidly generated from the current position, and one path of the random trees is selected to go to a target position. However, in the actual application process, the calculation load of the robot is increased by generating a large number of random trees by the RRT algorithm, so that the robot needs a large amount of time to perform data calculation, and the exploration efficiency of the robot is affected. Disclosure of Invention The application aims to provide an autonomous exploration method and device based on boundary and layering, which can improve the autonomous exploration efficiency of a robot. In order to achieve the above object, the present application provides the following solutions: In a first aspect, the present application provides an autonomous exploration method based on boundaries and layering, including: Acquiring environment information detected by a robot detection assembly and the current position of a robot; Constructing a two-dimensional grid map of a current detection area according to current environment information, and determining the state of each grid unit in the two-dimensional grid map, wherein the states of the grid units comprise an unknown area, an obstacle area and a free running area; Setting a dynamic sliding window according to the current position of the robot in the current two-dimensional grid map, wherein the size of the dynamic sliding window is determined according to the uncertainty of the environment, the distribution of obstacles and the movement speed of the robot; When a new boundary point is generated in the current dynamic sliding window, determining a target boundary point in each boundary point in the current dynamic sliding window, taking a non-target boundary point as a global boundary point, and deleting detected global boundary points in all current global boundary points, wherein the boundary points are grid units corresponding to a free running area bordering an unknown area; Using the target boundary point as a guide point, determining a feasible path from the current position of the robot to the target boundary point by using an RRT sampling algorithm to control the robot to move to the target boundary point according to the feasible path, and returning to the step of acquiring environment information detected by a robot detection component and the current position of the robot; When no new boundary point is generated in the current dynamic sliding window, selecting a target global boundary point from all the current undetected global boundary points, taking the target global boundary point as a target boundary point, returning to the step of using the target boundary point as a guide point, and determining a feasible path from the current position of the robot to the target boundary point by using an RRT sampling algorithm so as to control the robot to move to the target boundary point according to the feasible path. In a second aspect the application provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the computer program to implement the above-described boundary and hierarchy based autonomous exploration method. In a third aspect, the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the above-described boundary and hierarchy based autonomous exploration method. In a fourth aspect, the present application provides a computer program product comprising a computer program which, when executed by a processor, implements the above-described boundary and hierarchy based autonomous exploration method. According to the specific embodiment provided by the application, the application discloses the following technical effects: The application provides an autonomous exploration method and device based on boundary and layering, wherein a dynamic sliding window is arranged in a current two-dimensional grid map according to the current position of a robot, the size of the sliding window can be regulated and controlled