A method and system for path planning optimization

Abstract

The invention relates to a path planning optimization method, which divides the path search area into multiple grid nodes, determines the position coordinates of the starting point, target point and obstacle point, and creates an OPEN table and a CLOSE table, with the current node as the center. Expand outward layer by layer until there are obstacle points or target points in the expanded grid node layer, and use the A-star algorithm to determine the feasible grid node with the smallest total cost among all the grid nodes in the layer as the new current node , to determine whether the new current node is the target point, if not, repeat the above steps centering on the new current node, if yes, generate a path plan from the starting point to the target point through all current nodes in sequence. Compared with the traditional A-star algorithm, the present invention expands the search range, increases the angle of the optional grid nodes, makes the path smoother, reduces the number of running steps, and reduces the number of times to select the current node, thereby reducing the running time and improving the efficiency of path planning.

Description

technical field [0001] The present invention relates to the technical field of path planning, in particular to a path planning optimization method and system. Background technique [0002] Path planning refers to calculating the best or second-best track within a specified time through navigation technology based on preset or sudden terrain data, taking into account the error of terrain data and random factors in the environment (such as climate change, etc.) ), it is required to realize the dynamic correction of the path in the planning process in order to avoid the threat environment and complete the scheduled tasks smoothly. The path planning involved in the military field mainly includes automatic UAV track planning, missile threat avoidance, intelligent robot control, etc.; in the daily direction, it mainly includes urban intelligent traffic dynamic path planning, logistics, food delivery, etc. [0003] The algorithm of path planning is the core of path planning. The t...

AI Technical Summary

Problems solved by technology

The path search flow chart of the traditional A* algorithm is as follows: figure 2 As shown, although the traditional A* algorithm can plan a better track, it takes a long time to search the path, and the turning point of the search path is relatively abrupt, so it cannot meet the path planning of objects with weak maneuverability.

Images