Going upstairs is a common humanoid robot task. In this paper, a genetic algorithm (GA) gait synthesis method for going upstairs and a radial basis function neural network (RBFNN) implementation, are considered. The gait synthesis is analyzed based on the minimum consumed energy and minimum torque change. The proposed method can easily be applied to generate the angle trajectories for going downstairs, overcoming obstacles, etc. In our work, the stability is verified through the ZMP concept. For the real time implementation, a RBFNN which is taught based on the GA results, is considered. The RBFNN generates the optimal gait in a very short time, where the input variables are the step length, step height and step time. Simulations are realized based on the parameters of the “Bonten‐Maru I” humanoid robot.
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1 December 2001
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December 01 2001
Real time generation of humanoid robot optimal gait for going upstairs using intelligent algorithms Available to Purchase
Genci Capi;
Genci Capi
Genci Capi is a PhD student in the Department of Mechanical Systems Engineering, Yamagata University, Yonezawa, Japan.
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Yasuo Nasu;
Yasuo Nasu
Yasuo Nasu is a PhD student in the Department of Mechanical Systems Engineering, Yamagata University, Yonezawa, Japan.
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Leonard Barolli;
Leonard Barolli
Leonard Barolli is Research Associate, Department of Public Policy and Social Studies, Yamagata University, Yonezawa, Japan.
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Kazuhisa Mitobe;
Kazuhisa Mitobe
Kazuhisa Mitobe is a PhD student in the Department of Mechanical Systems Engineering, Yamagata University, Yonezawa, Japan.
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Mitsuhiro Yamano
Mitsuhiro Yamano
Mitsuhiro Yamano is a PhD student in the Department of Mechanical Systems Engineering, Yamagata University, Yonezawa, Japan.
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Publisher: Emerald Publishing
Online ISSN: 1758-5791
Print ISSN: 0143-991X
© MCB UP Limited
2001
Industrial Robot (2001) 28 (6): 489–497.
Citation
Capi G, Nasu Y, Barolli L, Mitobe K, Yamano M (2001), "Real time generation of humanoid robot optimal gait for going upstairs using intelligent algorithms". Industrial Robot, Vol. 28 No. 6 pp. 489–497, doi: https://doi.org/10.1108/EUM0000000006091
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