RRT-based Path Planning for Car-Like Vehicles with Nonholonomic Constraints

Abstract

In this paper, for car-like mobile robots, a novel path planning algorithm is proposed. The algorithm is based on rapidly-exploring random trees (RRT) with fixed nodes (RRT*FN). An improvement on the RRT*FN is proposed to abide by the non-holonomic motion constraints and RRT*FN non-holonomic (RRT*FN-NH) is introduced. The new path planning algorithm handles the non-holonomic constraints as well as the constraints on the velocity and acceleration of the vehicle. The performance of the proposed algorithm RRT*FN-NH is tested on two maps obtained from Google maps at three different speed profiles.