Motion Planning and Experimental Validation for an Autonomous Bicycle
Alen Turnwald, Steven Liu · 2019
Trajectory planning for an autonomous bicycle is investigated with regard to different vehicle models. To this end, a nonlinear optimization problem is set up using three models which differ with respect to the geometric details and, therefor, the included physical effects. First, using the method of Direct Collocation the optimization problem is transcribed with the vehicle models as equality constraints. The resulting trajectories are applied to the most detailed vehicle model using a 2-degree-of-freedom loop structure for validation and comparison. Further, a prototype autonomous two-wheeled vehicle is introduced which was developed for experimental verification of motion planning and control algorithms. Finally, experiments are presented and discussed that are run on the real vehicle for a particular maneuver. Thereby, the differences between the trajectories created by different vehicle models are emphasized.