A Shortest Smooth-path Motion Planning for a Mobile Robot with Nonholonomic Constraints

Abstract

This paper presents how to plan the shortest motion for a mobile robot with nonholonomic constraints. The proposed method uses the RRT* algorithm, the Potential Field algorithm, and Dubin Curves to create a path that can solve path planning problems. Firstly, the RRT* algorithm is used to find the shortest path by expanding the Tree in the global environment until reaching the goal region. Then, the resultant path is improved with Repulsive Force from the Potential Field algorithms that calculate the influence of static obstacles on the path for better obstacle avoidance. Finally, Dubins Curves is used to smooth the planned path with curves having the same radius, which helps handle nonholonomic constraints problems for Car-like mobile robot. The test method using simulation with MATLAB software is applied to prove that the proposed method can solve some typical path planning problems.