Real-time temporal adaptation of dynamic movement primitives for moving targets

Abstract

This work is aimed at extending the standard dynamic movement primitives (DMP) framework to adapt to real-time changes in the task execution time while preserving its style characteristics. We propose an alternative polynomial canonical system and an adaptive law allowing a higher degree of control over the execution time. The extended framework has a potential application in robotic manipulation tasks that involve moving objects demanding real-time control over the task execution time. The existing methods require a computationally expensive forward simulation of DMP at every time step which makes it undesirable for integration in realtime control systems. To address this deficiency, the behaviour of the canonical system has been adapted according to the changes in the desired execution time of the task performed. An alternative polynomial canonical system is proposed to provide increased real-time control on the temporal scaling of DMP system compared to the standard exponential canonical system. The developed method was evaluated on scenarios of tracking a moving target where the desired tracking time is varied in real-time. The results presented show that the extended version of DMP provide better control over the temporal scaling during the execution of the task. We have evaluated our approach on a UR5 robotic manipulator for tracking a moving object.