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Erschienen in: Natural Computing 4/2020

07.02.2019

Periodic motion generation for the impactless biped walking up slopes via genetic algorithm

verfasst von: Lulu Gong, Ruowei Zhao, Jinye Liang, Lei Li, Ming Zhu, Ying Xu, Xiaolu Tai, Xinchen Qiu, Haiyan He, Fangfei Guo, Jindong Yao, Zhihong Chen, Chao Zhang

Erschienen in: Natural Computing | Ausgabe 4/2020

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Abstract

The angular positions of the lower limb joints play important roles on the energy consumption and stability for the bipedal walking up slopes. In this study, the ranges of angular position of lower limb joints are confined and the velocity of swing foot is zero when it touches the ground, which result in the construction of the impactless planar bipedal model. Motion/force control scheme combined with genetic algorithm (GA) is used to ensure stability and low energy cost of bipedal walking at different speeds. The optimized parameters of gaits are obtained by GA, which include walking speed, step length and the maximum height of swing ankle joint. The results demonstrate that more energy is consumed when the optimal walking speed increases for the biped walking on slopes with the same gradient. There are no great differences in optimal step length of the biped when the walking speed changes. The optimal step length declines as the slope increases at the same walking speed. The ankle torques of standing leg have higher values in single support phase at fast speed compared to those at slow and normal speeds. Modifications of boundary conditions can not only be used to realize the stable walking for the biped negotiating slopes, but also be applied to analyze bipedal gaits for walking on stairs and uneven surfaces.

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Literatur
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Zurück zum Zitat Gumuscu A, Karadag K, Tenekeci ME, Aydilek IB (2017) Genetic algorithm based feature selection on diagnosis of Parkinson disease via vocal analysis. In: 2017 25th signal processing and communications applications conference (SIU), Antalya, Turkey. https://doi.org/10.1109/SIU.2017.7960384 Gumuscu A, Karadag K, Tenekeci ME, Aydilek IB (2017) Genetic algorithm based feature selection on diagnosis of Parkinson disease via vocal analysis. In: 2017 25th signal processing and communications applications conference (SIU), Antalya, Turkey. https://​doi.​org/​10.​1109/​SIU.​2017.​7960384
Zurück zum Zitat Taherkhorsandi M, Castillo-Villar KK, Mahmoodabadi MJ, Janaghaei F, Mortazavi Yazdi SM (2015) Optimal sliding and decoupled sliding mode tracking control by multi-objective particle swarm optimization and genetic algorithms. In: Azar AT, Zhu Q (eds) Advances and applications in sliding mode control systems, vol 576. Studies in computational intelligence. Springer, Cham, pp 43–78. https://doi.org/10.1007/978-3-319-11173-5_2CrossRef Taherkhorsandi M, Castillo-Villar KK, Mahmoodabadi MJ, Janaghaei F, Mortazavi Yazdi SM (2015) Optimal sliding and decoupled sliding mode tracking control by multi-objective particle swarm optimization and genetic algorithms. In: Azar AT, Zhu Q (eds) Advances and applications in sliding mode control systems, vol 576. Studies in computational intelligence. Springer, Cham, pp 43–78. https://​doi.​org/​10.​1007/​978-3-319-11173-5_​2CrossRef
Metadaten
Titel
Periodic motion generation for the impactless biped walking up slopes via genetic algorithm
verfasst von
Lulu Gong
Ruowei Zhao
Jinye Liang
Lei Li
Ming Zhu
Ying Xu
Xiaolu Tai
Xinchen Qiu
Haiyan He
Fangfei Guo
Jindong Yao
Zhihong Chen
Chao Zhang
Publikationsdatum
07.02.2019
Verlag
Springer Netherlands
Erschienen in
Natural Computing / Ausgabe 4/2020
Print ISSN: 1567-7818
Elektronische ISSN: 1572-9796
DOI
https://doi.org/10.1007/s11047-019-09733-x

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