Divide and Conquer Deterministic Path Optimization Algorithm

Abstract

The invention provides a divide-and-conquer certainty route optimization algorithm, and relates to the field of route planning. The divide-and-conquer certainty route optimization algorithm is characterized in that an environment map is divided into grids; each grid is in a blank state or an assigned state; the blank state means that the grids allow passing, and the assigned state means that the grids are blocked areas and do not allow pass; starting point and ending point positions are determined in blank grids which are arranged at intervals and provided with assigned grids at the intervals;an angular point force combining method is carried out to solve the angle point positions of grid blocks, and the angle point positions are marked; all marked angle points are pairwise connected; each feasible route is divided into M line sections; the length range of each line section is within a rectangle; the coordinate value of the four corners of the rectangle are rounded and processed; thecoordinate value of the four corners are compared with rectangle array coordinates generated by gridding treatment; whether each coordinate point is in the blank grid can be determined; the starting point is treated as a departing point, and the ending point is treated as a finishing point; the distance of each search route is compared, and the optimal route from the starting point to the ending point can be searched.

Description

technical field [0001] The invention relates to the field of path planning, and is specifically applied to accurately obtain the optimal path of a robot under complex obstacles. Background technique [0002] The advantage of grid path planning is that after the map is rasterized, obstacles can be divided into multiple small grids of fixed scale, so that the location, size and shape of obstacles can be accurately identified, making it easier for robots to avoid obstacles. However, after the map environment is rasterized, the selectable route can only be the four corners or the center point of the grid, and the vector connecting path between two targets cannot be directly selected, so the final path obtained is not the shortest path. Different from the grid path planning, in the vector path planning, the selected route can be the vector connection path of two target points, and there is no constraint that the grid path must pass through the grid center point. [0003] Traditi...

AI Technical Summary

Problems solved by technology

The disadvantage of this algorithm is that only by generating a large number of random feasible points can it be possible to obtain a path from the start point to the end point, and the complexity of the algorithm will increase with the increase of the number of feasible points, especially when there is a slit channel In the obstacle map of , once no random point falls in the slit, the PRM algorithm will not be able to search for a feasible path from the start point to the end point

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