A Predictive Path Planning Algorithm for Mobile Robot in Dynamic Environments Based on Rapidly Exploring Random Tree

Abstract

Path planning of mobile robot has always been a focus in the field of robotics for a long time, which is highly related to the ability of the robot to execute tasks. However, many traditional path planning algorithms are not suitable for the dynamic environments, which are more common in reality. In this paper, a predictive path planning algorithm for mobile robot in the dynamic environments is proposed based on the rapidly exploring random tree algorithm. Under the premise of pre-searching the global approximate optimal path, the algorithm introduces a simple movement prediction about the mobile robot itself and the dynamic obstacles according to their velocities and then re-plans the path against the dynamic obstacles, which accelerates the search speed of re-planning, reduces the path cost and the probability of collision, and improves the quality of the re-planning path. Computer simulations show the effectiveness and the superiority of the new strategy.