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.

弹性机械手通常是由于人机协作场景中的轻型结构或安全要求而产生的。在许多情况下，减振对于实现稳定和精确的操作是必不可少的，这对控制器提出了很高的要求。对于具有一般运动学且没有专用阻尼执行器的连杆弹性操纵器，一个根本的挑战是关节可能无法根据操纵器的配置来控制连杆的振动。许多控制概念都具有通过例如专用致动器或特殊运动学结构来控制振动的足够高的能力。这项工作提出了一种基于在线，基于优化的运动计划方法，其中采用了三种方法来最大化链弹性操纵器的这种能力。通过确定竞争目标的优先级和自适应激活来控制振动。该方法的有效性在具有3个激活的自由度和两个弹性链接的实际操纵器上得到了证明，该操纵器在不同的干扰情况下都可以使用。结果表明，由干扰引起的振动幅度衰减明显快于常规运动计划。