Robotic Arm C‐Space Trajectory Planning Using Large‐Scale Digital Twin Parallelism and Safety‐Prioritisable Optimal Search Algorithm

摘要

ABSTRACT This paper proposes a trajectory planning approach based on the configuration space (C‐space) generated from large‐scale digital twinning. Leveraging GPU‐based parallelism, the C‐space of a multi‐degree‐of‐freedom (multi‐DoF) manipulator in a complex task space with obstacles can be mapped out through extensive simulation of motion and collision of multiple virtual robot arms known as digital twins. An optimal search algorithm is incorporated with artificial potential field generated in the C‐space to allow the prioritising of safety in accordance with the varying risks associated with the obstacles by means of variable repulsive potential. To extend the high‐degree path to smooth and continuous joint trajectories, a spline operation is applied. Finally, a 7‐DOF physical manipulator is deployed for the execution of the planned trajectory in a task space filled with obstacles. Results demonstrated a 16.3% improvement in success rate achieved by utilising the safety‐prioritisable search algorithm. With this unified formulation of the control and planning problem in the C‐space, the kinematics complexity of a large DOF manipulator in obstacle‐present task space could be truly relieved from the joint control loop. This simplification, in turn, opens up prospective work in dynamic reconstruction of the C‐space.