2D-Span Resampling of Bi-RRT in Dynamic Path Planning

Abstract

Path planning is an essential task in robot soccer. The purpose of path planning brings a robot to quickly achieve a desired location, showing that the robot has a better chance to shoot or dribble a ball to a goal. Previous work in path planning adopted sensors such as sonars and lasers to obtain local information to avoid obstacles and reach to a goal. By doing this, the robot may move slowly and collide easily with other robots that using similar obstacle-avoidance algorithms. This work proposes a 2D-span resampling method and post processing including pruning and smoothening of bi-directional rapidly-exploring random tree (Bi-RRT) to improve the path route and computational time of path planning. To avoid obstacles, this work re-plans the path by a novel 2D-span resampling method in Bi-RRT. The post processing of pruning unnecessary Bi-RRT nodes and smoothening path route enables a robot to reach a goal with a short path. This simulations validate the proposed method by the performance comparison with several common path-planning methods, showing that it generally has a shorter route distance and less computational time than the other methods.

Keywords

• Path Planning
• Bi-Directional Rapidly-Exploring Random Tree (Bi-RRT)
• 2D-Span Resampling