Existing techniques for motion imitation often suffer a certain level of latency due to their computational overhead or a large set of correspondence samples to search. To achieve real-time imitation with small latency, we present a framework in this paper to reconstruct motion on humanoids based on sparsely sampled correspondence. The imitation problem is formulated as finding the projection of a point from the configuration space of a human's poses into the configuration space of a humanoid. An optimal projection is defined as the one that minimizes a back-projected deviation among a group of candidates, which can be determined in a very efficient way. Benefited from this formulation, effective projections can be obtained by using sparsely sampled correspondence, whose generation scheme is also introduced in this paper. Our method is evaluated by applying the human's motion captured by an RGB-depth (RGB-D) sensor to a humanoid in real time. Continuous motion can be realized and used in the example application of teleoperation.
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December 2017
Research-Article
Motion Imitation Based on Sparsely Sampled Correspondence
Shuo Jin,
Shuo Jin
Department of Mechanical and
Automation Engineering,
The Chinese University of Hong Kong,
Hong Kong 999077, China
e-mail: jerry.shuojin@gmail.com
Automation Engineering,
The Chinese University of Hong Kong,
Hong Kong 999077, China
e-mail: jerry.shuojin@gmail.com
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Chengkai Dai,
Chengkai Dai
Department of Mechanical and
Automation Engineering,
The Chinese University of Hong Kong,
Hong Kong 999077, China
e-mail: ckdai@mae.cuhk.edu.hk
Automation Engineering,
The Chinese University of Hong Kong,
Hong Kong 999077, China
e-mail: ckdai@mae.cuhk.edu.hk
Search for other works by this author on:
Charlie C. L. Wang
Charlie C. L. Wang
Department of Design Engineering and
TU Delft Robotics Institute,
Delft University of Technology,
Delft 2628, The Netherlands
e-mail: c.c.wang@tudelft.nl
TU Delft Robotics Institute,
Delft University of Technology,
Delft 2628, The Netherlands
e-mail: c.c.wang@tudelft.nl
Search for other works by this author on:
Shuo Jin
Department of Mechanical and
Automation Engineering,
The Chinese University of Hong Kong,
Hong Kong 999077, China
e-mail: jerry.shuojin@gmail.com
Automation Engineering,
The Chinese University of Hong Kong,
Hong Kong 999077, China
e-mail: jerry.shuojin@gmail.com
Chengkai Dai
Department of Mechanical and
Automation Engineering,
The Chinese University of Hong Kong,
Hong Kong 999077, China
e-mail: ckdai@mae.cuhk.edu.hk
Automation Engineering,
The Chinese University of Hong Kong,
Hong Kong 999077, China
e-mail: ckdai@mae.cuhk.edu.hk
Yang Liu
Charlie C. L. Wang
Department of Design Engineering and
TU Delft Robotics Institute,
Delft University of Technology,
Delft 2628, The Netherlands
e-mail: c.c.wang@tudelft.nl
TU Delft Robotics Institute,
Delft University of Technology,
Delft 2628, The Netherlands
e-mail: c.c.wang@tudelft.nl
1Corresponding author.
Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received August 16, 2016; final manuscript received May 2, 2017; published online June 15, 2017. Editor: Bahram Ravani.
J. Comput. Inf. Sci. Eng. Dec 2017, 17(4): 041009 (7 pages)
Published Online: June 15, 2017
Article history
Received:
August 16, 2016
Revised:
May 2, 2017
Citation
Jin, S., Dai, C., Liu, Y., and Wang, C. C. L. (June 15, 2017). "Motion Imitation Based on Sparsely Sampled Correspondence." ASME. J. Comput. Inf. Sci. Eng. December 2017; 17(4): 041009. https://doi.org/10.1115/1.4036923
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