Trajectory planning method with built-in trade-off mechanism for robot systems with an extended axis

Abstract

This paper proposes a trajectory planning method with a built-in trade-off mechanism for robot systems with extended axis. The proposed algorithm is designed to meet diverse requirements for operational efficiency and motion stability in various industrial scenarios. By establishing the dynamic model of an articulated robot, the dynamic equations are transformed into linear constraints in the parameter space. Based on the TOPP-RA, a trade-off parameter mechanism is introduced to reconstruct the upper bound of the controllable set, enabling users to flexibly adjust the balance between time-optimal and cruising motions. Furthermore, a motion allocation strategy is proposed to decouple the planned trajectory of the articulated robot from the motion of the expandable axis. Trajectory planning can be accomplished using only the geometric parameters of the expandable axis, thus avoiding complex dynamic modeling. Experimental results demonstrate that the proposed algorithm achieves a trade-off between cruising and time-optimal motion while taking into account computational efficiency, execution performance, and tracking accuracy.