Global path planning method based on weighted A * algorithm for expanding search neighborhood

Abstract

The invention discloses a global path planning method based on a weighted A * algorithm for expanding a search neighborhood, and the method comprises the steps: S1, carrying out the environment modeling according to the point cloud information collected by a sensor, and building a two-dimensional environment model through a grid method; S2, optimizing a target cost estimation function h (n) in anestimation function f (n) of path planning of a weighted A * algorithm for expanding a search neighborhood, adding distance information and angle information, and performing weighted measurement; S3,expanding the searchable neighborhood of the current node of the A * algorithm; and S4, according to the searchable neighborhood obtained in the step S3 and the estimation function cost value of the calculation A * algorithm defined in the step S2, sequentially selecting the node with the minimum global estimation cost value as the next node until the target point, so that the path is the shortestpath. By designing the new heuristic function and expanding the operation of searching the neighborhood, the optimized A * algorithm is more excellent in path length, better in smoothness and shorterin path finding time compared with the original algorithm, and can be suitable for the situation with many obstacles.

Description

technical field [0001] The invention relates to the technical field of path planning, in particular to a global path planning method based on the improved A* algorithm. Background technique [0002] Global path planning is one of the important contents of mobile robot navigation research. It refers to planning an effective path for the robot from the start point to the end point after environment modeling based on complete prior information, and ensuring that the robot does not collide with obstacles in the map. . [0003] The grid method converts the characteristic information of the robot's operating environment into a unit grid with binary information, which has significant advantages in environment modeling because of its simplicity and ease of handling. [0004] The A* algorithm is a search algorithm with heuristic features, which is widely used to solve static global path planning problems because of its simplicity, high efficiency, strong operability and high accurac...

AI Technical Summary

Problems solved by technology

However, the A* algorithm is affected by the node search strategy, and the movement angle is limited to an integer multiple of 45°. There are defects that the planned path is not the theoretically optimal path, there are too many inflection points, and the algorithm search efficiency is reduced when the environmental information is too complex.

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