Manipulating deformable linear objects: Sensor-based skills of adjustment motions for vibration reduction

Abstract

The vibration of a deformable object is often problematic during automatic handling by robot manipulators. However, humans can often handle and damp the vibration of deformable objects with ease. This paper presents forcestorque sensor-based skills for handling deformable linear objects in a manner suitable to reduce acute vibration with simple human skill inspired strategies that consist of one or two adjustment motions. The adjustment motion is a simple open-loop motion that can be attached to the end of any arbitrary end-effector's trajectory. As an ordinary industrial robot's simple action, it has three periods, i.e., acceleration, constant speed, and deceleration period; it starts from a predicted time tightly close to a forcesmoment maximum. The predicted time for the adjustment action is generated automatically on-line based on the vibration rhythm and the data sensed by a forcestorque sensor mounted on the robot's wrist. To find the matching point between the vibrational signal of the deformable object and a template, template matching techniques including cross-correlation and minimum squared error methods are used and compared. Experiments are conducted with an industrial robot to test the new skills under various conditions. The results demonstrate that an industrial robot could perform effective vibration reduction skills with simple strategies. © 2005 Wiley Periodicals, Inc.