Dynamic path planning method for mobile robot

Abstract

The invention is applicable to the technical field of automatic control, and provides a dynamic path planning method for a mobile robot, comprising the following steps: calculating a distance betweenall the node pairs on a grid map by a Floyd algorithm; when a new issued task is detected, planning a path of the task by an improved A* algorithm; checking whether there is an obstacle on a next nodeof the path when the robot walks along the planned path, if not, making a step forward, if any, adding the next node in a close table, and rapidly planning a path from the current node to a target point by the improved A* algorithm; repeating the previous step until the robot reaches the target point. Based on a calculation result from the Floyd algorithm, the dynamic path planning method of theinvention improves a heuristic function of the A* algorithm, and applies the A* algorithm in the dynamic path planning scene of a continuous task of the mobile robot. By using the improved A* algorithm, the path is re-planned only when a dynamic obstacle appears on the path, thereby greatly reducing computational cost and greatly improving real-time of the robot in operation.

Description

technical field [0001] The invention is applicable to the technical field of automatic control, and in particular relates to a dynamic path planning method of a mobile robot. Background technique [0002] There are two types of obstacles in the map environment where the robot actually operates, one is fixed obstacles, and the other is random obstacles that appear over time. Path planning refers to selecting a path from the starting point to the goal point under the given environmental obstacle conditions, so that the robot can pass through all obstacles safely and without collision. This method of autonomously avoiding obstacles and completing tasks is an important content in the research and application of robots. [0003] For the map of static obstacles, common robot path planning methods include A* algorithm, Dijkstra algorithm, genetic algorithm, particle swarm algorithm and artificial potential field method, etc. Among them, the A* algorithm has the lowest complexity, ...

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Problems solved by technology

[0003] For the map of static obstacles, common robot path planning methods include A* algorithm, Dijkstra algorithm, genetic algorithm, particle swarm algorithm and artificial potential field method, etc. Among them, the A* algorithm has the lowest complexity, and the amount of calculation is relatively small compared to other algorithms. Small, but on the current embedded robot, using the A* algorithm for real-time path planning, the amount of calculation is still too large, so it is necessary to further improve the A* algorithm to improve its planning efficiency

Moreover, on a symmetrical map, or a map with a large number of equidistant paths between nodes, the path planning effect of the A* algorithm is often poor.

In addition, the above path planning methods only consider the avoidance of static obstacles, and seek the shortest path on this basis. If there are dynamically appearing obstacles in the map, these methods cannot solve the problem.

[0004] For the avoidance of dynamic obstacles, the current common methods include rolling window method and model prediction method, etc., but these methods pay too much attention to the local dynamic information of the map, the amount of calculation is large, and the consideration of global optimality is slightly insufficient

In addition, the current mobile robots generally operate continuously on a basically fixed map scene, and the existing path planning algorithms generally do not take advantage of this operating characteristic of the robot

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