Function-Parameterized Optimal Trajectory Generation for Mobile Robots*

Spline-based trajectory generation methods are widely used in the field of industrial machines. Here, objectives like workpiece accuracy or efficiency come very close to those for mobile robots covering a predefined area. Therefore, this work is motivated by spline-based trajectory generation methods for industrial machines. Splines have several advantages for trajectory generation as they are capable of fitting highly complex profiles. Moreover, they are smooth, continuous and admit for analytical derivatives. A novel optimization approach is introduced to generate time-optimal coverage motion for mobile robots. The novelty of this method is to exploit spline properties to ensure that the robot stays within a predefined tolerance corridor around a reference path. In addition, the kinematic model of the mobile robot is considered to guarantee a physically feasible trajectory. The proposed optimization framework replaces rectilinear corner paths by smooth trajectories, admits the kinematic model and satisfies control input and kinematic limits. The resulting trajectories are compared to a state-of-theart optimal control approach using a direct collocation method. The results show that the presented method outperforms the state-of-the-art approach in terms of motion time. Furthermore, smoother trajectory is achieved.