Trajectory Planning for Car-Like Robots using Rapidly Exploring Random Trees*

This work presents the RRT-planning algorithm adapted to a mobile car-like robot. Based on an short overview of the RRT-approach, all necessary components, adapted to target vehicle, are shown. A possible state space model, including a valid metric, is presented, as well as a control input selection approach. In order to avoid undesired circular motion, we introduced a circle limitation for the control input selection algorithm. Several simulation results are presented for different environments. We show the limitation and propose a solution implementing this algorithm on real hardware. Finally a conclusion is drawn, summarizing the results and giving an outlook to future work.