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A Stable Gait Planning Method of Biped Robot Based on Ankle motion Smooth Fitting

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Abstract

In ankle joint trajectory planning of biped robots, the spline interpolation generally leads to acceleration mutations on the key points, which weakens the stability of the biped robot. To solve this problem, a smooth function fitting method on ankle joint trajectory planning is proposed in this paper. In this method, the higher order derivatives of the ankle joint trajectory is smooth, and the acceleration mutation can be avoided. The biped robot gait planning of a whole cycle is accomplished by calculating the joint angle sequences of hip, knee and ankle. The effectiveness of the proposed method is demonstrated by numerical simulations on NAO robot gait planning. Experimental results show that the proposed method can improve the stability of the zero moment point (ZMP) margin effectively when it is applied to the bipedal robot gait planning on the non-horizontal ground.

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Author information

Authors and Affiliations

  1. Tianjin Key Laboratory For Control Theory & Applications in Complicated SystemsSchool of Electrical Engineering Tianjin University of Technology, Tianjin, China

    En Zeng Dong, Dan Dan Wang, Ji Gang Tong & Chao Chen

  2. School of Automation, University of South Africa, Florida, 1710, South Africa

    Zeng Hui Wang

Authors
  1. En Zeng Dong
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  2. Dan Dan Wang
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  3. Ji Gang Tong
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  4. Chao Chen
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  5. Zeng Hui Wang
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Corresponding authors

Correspondence to Ji Gang Tong or Chao Chen.

Additional information

Recommended by Associate Editor Sooyeong Yi under the direction of Editor Hyun-Seok Yang. This paper was supported by the National Natural Science Foundation (61203138); The Foundation of the Application Base and Frontier Technology Research Project of Tianjin (15JCYBJC51800); The City of Tianjin Higher School Science and Technology Development Fund Planning Project (20120829) and South African National Research Foundation Incentive Grants (No. 81705).

Dong En Zeng received the Doctoral degree in Opertional Research and Cybernetics, Nankai University, Tianjin, China in 2006. Currently, he is a Professor in School of Electrical Engineering, Tianjin University of Technology. He is mainly working on intelligent control theory and applications, image and video processing, and brain-computer interface (BCI).

Wang Dan Dan received her Bachelor degree in electrical engineering and automation from Hebei University of Agricultural, China, in 2014. She was a graduate student at Tianjin Univercity of Technology in control science and Engineering in 2014. Her research interests include control applications, biped robot gait planning, and human-robot interaction, and so on.

Tong Ji Gang received the B.S. degree from Liaoning University of Technology, Jinzhou, China, in 1998, and the M.S. and Ph.D degrees in control engineering from NanKai University, TianJin, China, in 2006 and 2010, respectively. Currently, he is a teacher at the School of Electrical Engineering, Tianjin University of Technology. His research interests include embedded system, human-computer interaction techniques.

Chen Chao received his Bachelor degree in Automation, and his Master degree in Pattern Recognition and Intelligent System from Northeastern University, Shenyang, China in 2005 and 2008. In 2014, He got his Ph.D. degree from Tokyo Institute of Technology, Japan. Currently, he is an Associate professor in School of Electrical Engineering, Tianjin University of Technology. He mainly works on invasive and non-invasive brain-computer interface (BCI), pattern recognition and intelligent algorithm.

Wang Zeng Hui graduated with Doctoral degree in Control Theory and Control Engineering, Nankai University, China in 2007. He is currently a Professor in the Department of Electrical and Mining Engineering at University of South Africa. He has about 70 peer-reviewed journal and conference publications. His research interest is in the fields of evolutionary optimization, image and video processing, adaptive control and predictive control for nonlinear systems, artificial Intelligence, and so on.

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Dong, E.Z., Wang, D.D., Tong, J.G. et al. A Stable Gait Planning Method of Biped Robot Based on Ankle motion Smooth Fitting. Int. J. Control Autom. Syst. 16, 284–294 (2018). https://doi.org/10.1007/s12555-016-0263-8

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  • DOI: https://doi.org/10.1007/s12555-016-0263-8

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