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• W2546861332 abstract "Humans can perform natural and robust walking behavior. They can even quickly adapt to different situations, like changing their walking speed to synchronize with the speed of a treadmill. Reproducing such complex abilities with artificial bipedal systems is still a difficult problem. To tackle this problem, we present here an adaptive combinatorial neural control circuit consisting of reflex-based and central pattern generator (CPG)-based mechanisms. The reflex-based control mechanism basically generates energy-efficient bipedal locomotion while the CPG-based mechanism with synaptic plasticity ensures robustness against loss of global sensory feedback (e.g., foot contact sensors) as well as allows for adaptation within a few steps to deal with environmental changes. We have successfully applied our control approach to the biomechanical bipedal robot DACBOT. As a result, the robot can robustly walk with energy efficiency and quickly adapt to different speeds of a treadmill." @default.
• W2546861332 created "2016-11-11" @default.
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• W2546861332 date "2016-01-01" @default.
• W2546861332 modified "2023-09-25" @default.
• W2546861332 title "Adaptive Combinatorial Neural Control for Robust Locomotion of a Biped Robot" @default.
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• W2546861332 doi "https://doi.org/10.1007/978-3-319-43488-9_28" @default.
• W2546861332 hasPublicationYear "2016" @default.
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