Kinodynamic Motion Planning of a Skid-Steering Mobile Robot Using RRTs

Abstract

Motion planning is one of the fundamental problems in autonomous robotic navigation. However, usually the dynamic model of the robot is not considered on most of the basic motion planners, resulting in trajectories that may be difficult to be tracked by real robots. This paper describes the sampling-based Kino dynamic motion planning of a skid-steering mobile robot using the Rapidly-exploring Random Tree (RRT) method. Experimental results using a Pioneer 3-AT are presented. As a consequence of using the kinematic and dynamic model of the robot for planning, a simple proportional controller could be used to track the generated trajectory.