Abstract
For robots using legged locomotion, mathematical models of Central Pattern Generators (CPGs) are being used for controlling the complicated gaits and timing required for stable walking. Traditionally, these models are precisely designed for oscillation at a set of specific frequencies and phase relationships, which while easier to design is not conducive to robust and stable walking.
This work was funded by National Science Foundation (NSF) Award #1704366.
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Nourse, W., Quinn, R.D., Szczecinski, N.S. (2018). An Adaptive Frequency Central Pattern Generator for Synthetic Nervous Systems. In: Vouloutsi , V., et al. Biomimetic and Biohybrid Systems. Living Machines 2018. Lecture Notes in Computer Science(), vol 10928. Springer, Cham. https://doi.org/10.1007/978-3-319-95972-6_38
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DOI: https://doi.org/10.1007/978-3-319-95972-6_38
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