An optimization-based approach for elasticity-aware trajectory planning of link-elastic manipulators

Abstract Elastic manipulators often result from lightweight construction or safety requirements in human–robot-collaboration scenarios. In many cases, vibration-damping becomes necessary to enable stable and precise operation, which imposes high demands on controllers. A fundamental challenge for link-elastic manipulators with general kinematics and no dedicated damping actuators is the potential inability of a joint to control the vibration of a link depending on the manipulator’s configuration. Numerous control concepts assume a sufficiently high ability to control vibrations by, for example, dedicated actuators or special kinematic structures. This work presents an online, optimization-based motion planning approach with three methods for maximizing this ability for link-elastic manipulators. The planning algorithm utilizes modified cost functions to incorporate the controllability of vibrations by prioritization and adaptive activation of competing objectives. The effectiveness of the approach is demonstrated on a real manipulator with 3 actuated DoFs and two elastic links in different disturbance scenarios. The results show that the amplitudes of vibrations caused by disturbances decay noticeably faster than with conventional motion planning.