A dynamic variable sampling area rrt path planning method for unmanned vehicles

Abstract

The invention relates to a method for planning a route of an unmanned vehicle based on a rapidly expanding random tree (RRT) based on a dynamically variable sampling area for biasing a probability target. The method includes: first, initializing the map information, judging the area according to the dynamic variable sampling area formula; on this basis, performing collision detection with a reserved safety distance, and generating new nodes according to the probability target bias formula and the step size selection formula , repeat the above steps until the distance between the newborn node and the target node is less than the distance threshold, reverse search, and output the path; finally, consider the maximum rotation angle constraint to perform reverse optimization and third-order B-spline curve fitting optimization on the output path, Simulation verifies the effectiveness of the method. The invention can reduce the blindness and randomness of node search, reduce the time of path search, and the planned path smoothly conforms to the dynamic constraints of vehicle motion.

Description

technical field [0001] The invention relates to a path planning method for an unmanned vehicle based on a rapidly expanding random tree (RRT) algorithm for dynamically variable sampling areas, and belongs to the field of path planning for unmanned vehicles. Background technique [0002] With the continuous development of science and technology, unmanned vehicles are widely used in the military field, including material transportation, dangerous operations, special tasks, etc., but there are still deficiencies in the path planning of unmanned vehicles, such as slow planning speed and difficult overall planning and other shortcomings. [0003] In view of the above shortcomings, a variety of path planning algorithms have been applied to the path planning of unmanned vehicles. The commonly used path planning algorithms include ant colony algorithm, genetic algorithm, A* algorithm, RRT algorithm, etc. The RRT algorithm is widely used in the path planning of unmanned vehicles due...

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Problems solved by technology

[0002] With the continuous development of science and technology, unmanned vehicles are widely used in the military field, including material transportation, dangerous operations, special tasks, etc., but there are still deficiencies in the path planning of unmanned vehicles, such as slow planning speed and difficult overall planning and other shortcomings

[0004] (1) The discontinuity of the path. Due to the blindness and randomness of node search in the traditional RRT algorithm, it is easy to cause discontinuity and twists and turns in the planned path of the unmanned vehicle, which does not meet the dynamic constraints of the unmanned vehicle itself;

[0005] (2) Local optimal problem, the conventional RRT algorithm based on a single target bias is likely to cause the algorithm to oscillate near obstacles, resulting in local optimal and regional stagnation problems

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