Development of a DDP-based trajectory generation method considering the manipulability measure for 6-DOF collaborative robots

Abstract

Abstract This paper presents a trajectory generation method for 6-degrees-of-freedom (DOF) collaborative robots using the differential dynamic programming algorithm, integrating the manipulability measure (MM) to effectively avoid singularities. Traditional trajectory generation methods often neglect the robot’s dynamics, leading to non-optimized trajectories and potential singularity issues. Our approach integrates MM into the differential dynamic programming algorithm, ensuring consideration of the robot’s dynamics while effectively avoiding singularities. The proposed algorithm is applied to the 6-DOF collaborative robot RB1-500e and validated on the actual robot. The results demonstrate that the proposed method significantly improves trajectory generation and singularity avoidance compared to traditional methods. This study offers a robust solution that enhances both efficiency and safety in dynamic trajectory planning for collaborative robots.