Energy budgets for coordinate invariant robot control in physical human–robot interaction

Author:

Lachner Johannes12,Allmendinger Felix2,Hobert Eddo1,Hogan Neville34,Stramigioli Stefano15

Affiliation:

1. Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands

2. KUKA Deutschland GmbH, Zugspitzstraße 140, Augsburg, Germany

3. Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

4. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

5. International Laboratory of Biomechatronics and Energy-efficient Robotics, ITMO University, St. Petersburg, Russia

Abstract

In this work we consider the current certification process of applications with physical human–robot interaction (pHRI). Two major hazards are collisions and clamping scenarios. The implementation of safety measures in pHRI applications typically depends strongly on coordinates, e.g., to monitor the robot velocity or to predict external forces. We show that the current certification process does not, in general, guarantee a safe robot behavior. In particular, in unstructured environments it is not possible to predict all risks in advance. We therefore propose to control the energy of the robot, which is a coordinate invariant entity. For an impedance controlled robot, the total energy consists of potential energy and kinetic energy. The energy flow from task description to physical interaction follows a strict causality. We assign a safe energy budget for the robot. With this energy budget, the presented controller auto-tunes its parameters to limit the exchanged kinetic energy during a collision and the potential energy during clamping scenarios. In contact, the robot behaves compliantly and therefore eliminates clamping danger. After contact, the robot automatically continues to follow the desired trajectory. With this approach the number of safety-related parameters to be determined can be reduced to one energy value, which has the potential to significantly speed up the commissioning of pHRI applications. The proposed technique is validated by experiments.

Funder

Horizon 2020 Framework Programme

Centers for Mechanical Engineering Research and Education at MIT and SUSTech

Publisher

SAGE Publications

Subject

Applied Mathematics,Artificial Intelligence,Electrical and Electronic Engineering,Mechanical Engineering,Modelling and Simulation,Software

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