Human robot cooperation with compliance adaptation along the motion trajectory

• Published in: Autonomous robots Vol. 42; no. 5; pp. 1023 - 1035
• Main Authors: Nemec, Bojan, Likar, Nejc, Gams, Andrej, Ude, Aleš
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2018; Springer Nature B.V
• Subjects: Adaptation; Artificial Intelligence; Computer Imaging; Control; Cooperation; Decoupling; Engineering; Human behavior; Human motion; Mechatronics; Pattern Recognition and Graphics; Robot dynamics; Robot learning; Robotics; Robotics and Automation; Robots; Special Issue: Learning for Human-Robot Collaboration; Stiffness; Trajectories; Vision; Robot learning; Dynamic motion primitives; Learning by demonstration; Robot control; Human robot coordination
• ISSN: 0929-5593; 1573-7527
• DOI: 10.1007/s10514-017-9676-3

In this paper we propose a novel approach for intuitive and natural physical human–robot interaction in cooperative tasks. Through initial learning by demonstration, robot behavior naturally evolves into a cooperative task, where the human co-worker is allowed to modify both the spatial course of motion as well as the speed of execution at any stage. The main feature of the proposed adaptation scheme is that the robot adjusts its stiffness in path operational space, defined with a Frenet–Serret frame. Furthermore, the required dynamic capabilities of the robot are obtained by decoupling the robot dynamics in operational space, which is attached to the desired trajectory. Speed-scaled dynamic motion primitives are applied for the underlying task representation. The combination allows a human co-worker in a cooperative task to be less precise in parts of the task that require high precision, as the precision aspect is learned and provided by the robot. The user can also freely change the speed and/or the trajectory by simply applying force to the robot. The proposed scheme was experimentally validated on three illustrative tasks. The first task demonstrates novel two-stage learning by demonstration, where the spatial part of the trajectory is demonstrated independently from the velocity part. The second task shows how parts of the trajectory can be rapidly and significantly changed in one execution. The final experiment shows two Kuka LWR-4 robots in a bi-manual setting cooperating with a human while carrying an object.