Singularity Avoidance with Application to Online Trajectory Optimization for Serial Manipulators

Understand

This work proposes a novel singularity avoidance approach for real-time trajectory optimization based on known singular configurations.

• The focus of this work lies on analyzing kinematically singular configurations for three robots with different kinematic structures, i.e., the Comau Racer 7-1.4, the KUKA LBR iiwa R820, and the Franka Emika Panda, and exploiting these configurations in form of tailored potential functions for singularity avoidance.
• Monte Carlo simulations of the proposed method and the commonly used manipulability maximization approach are performed for comparison.
• The numerical results show that the average computing time can be reduced and shorter trajectories in both time and path length are obtained with the proposed approach