Path planning method based on concentric circle sampling guide RRT algorithm

Abstract

The invention relates to a path planning method based on a concentric circle sampling guide RRT algorithm. The method comprises the following steps of: 1, taking the starting point of path planning asthe root node of a random tree; 2, generating a random point by concentric circle sampling; 3, judging whether the random point is in a map range or not, if so, turning to the step 4, otherwise, returning to the step 2 to regenerate a random point; 4, finding out a node closest to the random point as an adjacent point; 5, generating a new node by extending step length from the adjacent point to the random point; 6, judging whether an obstacle exists between the new node and the adjacent point or not, if so, returning to the step 2 to perform resampling, and otherwise, adding the new node intothe random tree; 7, judging whether the new node is in a target point area or not, if so, adding a target point into the random tree, backtracking from the target point to the root node to obtain thepath points of a planned path, and otherwise, returning to the step 2; and 8, fitting the path points to obtain a final path. The method is beneficial to improving path finding efficiency and quicklyfinding the planned path.

Description

technical field [0001] The invention relates to the field of path planning, in particular to a path planning method based on concentric circle sampling guided RRT algorithm. Background technique [0002] In a complex environment, how to quickly and efficiently reach the target position safely from the starting position has attracted the attention of many scholars. Path planning is the key technology of this problem, and its main task is to find a continuous collision-free path from the initial state point to the target state point in space, while satisfying the corresponding constraints. [0003] Commonly used path planning algorithms include intelligent path planning algorithms, graph search algorithms, and heuristic search algorithms. Heuristic search algorithm, such as A* algorithm, based on the grid map, evaluates each searched position to find the best position, and then searches from this position until the target point position is searched. [0004] Rapidly-explorin...

AI Technical Summary

Problems solved by technology

However, because the RRT algorithm adopts a uniform sampling strategy and lacks guidance information, the calculation amount of the algorithm is large, which affects the speed of the algorithm; in addition, the target point appears in the sampling point as a random point with a certain probability, which can improve the planning efficiency, but It may also lead to falling into a local minimum, and eventually no path can be found under a certain time or number of iterations

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