Robot path planning method and device based on improved artificial potential field method

Abstract

The invention provides a robot path planning method and device based on an improved artificial potential field method. The method comprises the steps that an initial starting point and a final targetpoint of a robot and a decision time window length and window duration of the robot are determined, and an initial value of a time hand is set as a first decision time window period; a local startingpoint and a local target point at which the robot needs to reach are determined in a time window of the time hand, and a potential field of the surrounding environment is generated based on the improved artificial potential field method; the robot is driven to move according to the potential field of the surrounding environment, and the robot reaches the local target point from the local startingpoint in the time window of the time hand; and whether the local target point is a final target point to be reached by the robot or not is determined, if yes, path planning is completed, if not, the time hand is set to be the next decision time window period of the robot, and the next round cycle is continue to be executed. According to the technical scheme, the robot is driven to effectively avoid obstacle positions and quickly reach a target position.

Description

technical field [0001] The invention relates to the technical field of robot path planning, in particular to a robot path planning method and device based on an improved artificial potential field method. Background technique [0002] At present, intelligent robot technology has been developed rapidly, and the implementation of path planning and navigation is an essential function of mobile robots. In a complex environment, it is particularly important for the robot to use a simple, efficient and practical path planning algorithm. [0003] How to enable the robot to carry radar and other devices to detect the surrounding environment, and plan a path planning method that can avoid obstacles and reach the target position as quickly as possible according to the environmental information is a hot issue in the research of intelligent robot technology. The dynamic window neural network algorithm commonly used in the prior art has relatively complex operations, and the traditional...

AI Technical Summary

Problems solved by technology

The dynamic window neural network algorithm commonly used in the prior art has relatively complicated calculations, and the traditional artificial potential field method is often prone to fall into the problem of local minima in the application

Therefore, the algorithm of path planning in the prior art has complex calculations, which solves the problem of poor effectiveness of path planning in complex environments

Images