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Technical Brief

Enhanced Whole-Arm Robot Teleoperation Using a Semi-Autonomous Control Policy

[+] Author and Article Information
Hsien-I Lin

Graduate Institute of Automation Technology,
National Taipei University of Technology,
Taipei 10608,Taiwan
e-mail: sofin@ntut.edu.tw

Chi-Li Chen

Graduate Institute of Automation Technology,
National Taipei University of Technology,
Taipei 10608,Taiwan

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received August 2, 2012; final manuscript received December 12, 2013; published online February 19, 2014. Assoc. Editor: Alexander Leonessa.

J. Dyn. Sys., Meas., Control 136(3), 034502 (Feb 19, 2014) (6 pages) Paper No: DS-12-1257; doi: 10.1115/1.4026310 History: Received August 02, 2012; Revised December 12, 2013

Previous work in robot teleoperation focused on the movement of a robot's end-effector by a human operator. However, a lack of pose control in teleoperation resulted in the robot arm frequently colliding with obstacles. Furthermore, even with pose control, it is still difficult for the robot to quickly and accurately move to the target due to mechanical discrepancies between human and robot. This paper proposes a semi-autonomous method to teleoperate the robot arm by integrating whole-arm teleoperation in joint-space control and autonomous end-effector position control. The proposed method is validated through experimental work on a robot arm with 6 degrees of freedom, with results showing significant improvement in human control for reaching for objects safely, quickly, and accurately.

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Figures

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Fig. 1

Control modes of the proposed semi-autonomous system

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Fig. 2

Distance margin of safety controlled by the semi-autonomous control policy, (a) The control points defined by the semi-autonomous control policy, and (b) the distance sections represented by the defined points, A, B, and C

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Fig. 3

State machine of the proposed semi-autonomous control policy

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Fig. 4

Twelve markers placed to capture the human arm motion

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Fig. 5

Task environment. The robot was asked to pick up the apple while avoiding (a) a gray box in experiment A and (b) a transparent box in experiment B

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Fig. 6

Experiment C: robot was asked to pick up the ping-pong ball on the right-hand side and place it in the cup on the other side

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