Optimizing motion of robotic manipulators in interaction with human operators

  • Authors:

  • Hao Ding;Kurniawan Wijaya;Gunther Reißig;Olaf Stursberg

  • Affiliations:

  • Institute of Control and System Theory, Dept. Elect. Eng. and Comput. Sci., University of Kassel, Germany;Institute of Control and System Theory, Dept. Elect. Eng. and Comput. Sci., University of Kassel, Germany;Chair of Control Eng. (LRT-15), Dept. Aerospace Eng., University of the Federal Armed Forces Munich, Germany;Institute of Control and System Theory, Dept. Elect. Eng. and Comput. Sci., University of Kassel, Germany

  • Venue:
  • ICIRA'11 Proceedings of the 4th international conference on Intelligent Robotics and Applications - Volume Part I
  • Year:
  • 2011

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Abstract

Recently, the problem of how to manipulate industrial robots that interact with human operators attracts a lot of attention in robotics research. This interest stems from the insight that the integration of human operators into robot based manufacturing systems may increase productivity by combining the abilities of machines with those of humans. In such a Human-Robot-Interaction (HRI) setting, the challenge is to manipulate the robots both safely and efficiently. This paper proposes an online motion planning approach for robotic manipulators with HRI based on model predictive control (MPC) with embedded mixed-integer programming. Safety-relevant regions, which are potentially occupied by the human operators, are generated online using camera data and a knowledge-base of typical human motion patterns. These regions serve as constraints of the optimization problem solved online to generate control trajectories for the robot. As described in the last part of the paper, the proposed method is realized for a HRI scenario.