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Human-robot interaction detection: a wrist and base force/torque sensors approach

Published online by Cambridge University Press:  28 February 2006

Shujun Lu,
Jae H. Chung and
Stevens A. Velinsky
Shujun Lu
Affiliation:
Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030 (USA). E-mail: slu@stevens.edu, jchung3@stevens.edu
Jae H. Chung
Affiliation:
Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030 (USA). E-mail: slu@stevens.edu, jchung3@stevens.edu
Stevens A. Velinsky
Affiliation:
Department of Mechanical and Aeronautical Engineering, University of California at Davis, Davis, CA 95616 (USA). E-mail: savelinsky@ucdavis.edu
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Abstract

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In this paper, a collision detection and identification method of a manipulator, using wrist and base force/torque sensors, is presented. An impact model is used to simulate the interaction between the manipulator and the human or environment. A neural network approach and a model based method are developed to detect the collision forces and disturbance torques on the joints of the manipulator. The experimental results illustrate the validity of the developed collision detection and identification scheme.

Keywords

CollisionDetectionIdentificationBase and wrist force/torque sensorHumanManipulator

Information

Type
Article
Information
Robotica , Volume 24 , Issue 4 , July 2006, pp. 419 - 427
Copyright
2006 Cambridge University Press