Local path planning method based on obstacle self-protection artificial potential field method of particle swarm algorithm

Abstract

The invention provides a local path planning method based on an obstacle self-protection artificial potential field method of a particle swarm algorithm. According to the invention, the particle swarm algorithm is introduced, the turning constraint of the minimum turning radius existing in the turning process of an intelligent vehicle is combined, that is, the constraint of the maximum turning angle is added in the optimization process, curve optimization is carried out on a preliminarily planned path, a corresponding fitness function is established, a particle swarm algorithm is further adopted to limit an optimization range and find a course angle conforming to the steering characteristics of the intelligent vehicle, and the optimal course angle is obtained through continuous iteration of particles, so that a particle swarm obstacle self-protection artificial potential field method is established to avoid obstacles, and an optimal path conforming to the steering constraints of the intelligent vehicle is found.

Description

technical field [0001] The invention belongs to the technical field of intelligent driving path planning and autonomous navigation, local path planning for obstacle avoidance of unmanned vehicles and mobile robots, and in particular relates to a partial path planning method based on particle swarm algorithm for self-protection of obstacles using artificial potential field method. Background technique [0002] In recent years, with the development of computer technology, automobiles have gradually developed towards the direction of intelligence combined with electronic technology and network communication. Smart cars are conducive to improving traffic safety, reducing road congestion, improving social efficiency, and advocating low-carbon life. The key technologies of intelligent vehicles include environment perception, navigation and positioning, path planning and decision-making control, etc., and path planning is a key part of intelligent vehicles, which is of great signifi...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a local path planning method of obstacle self-protection artificial potential field method based on particle swarm algorithm. Factors solve the problem of unreachable targets, and propose an obstacle self-protection artificial potential field method based on the particle swarm algorithm to solve the path planning problem of multiple obstacles in a static environment. In order to obtain the optimal rotation angle of the smart car, the invention introduces the particle swarm Algorithm, combined with the turning constraint of the minimum turning radius in the turning process of the smart car, that is, adding the constraint of the maximum steering angle in the optimization process, performing curve optimization on the initially planned route, and establishing a corresponding fitness function, and further adopting particle swarm optimization The algorithm limits the optimization range and finds the heading angle that conforms to the steering characteristics of the smart car. The optimal heading angle is obtained through continuous iteration of the particles, so as to establish the particle swarm obstacle self-protection artificial potential field method to avoid obstacles, and find the steering constraints that meet the smart car. the optimal path of

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