Neuromorphic control of stepping pattern generation: a dynamic model with analog circuit implementation

Yang, Zhijun, Cameron, Katherine, Lewinger, William, Webb, Barbara and Murray, Alan (2012) Neuromorphic control of stepping pattern generation: a dynamic model with analog circuit implementation. IEEE Transactions on Neural Networks and Learning Systems, 23 (3). pp. 373-384. ISSN 2162-237X

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Abstract

Animals such as stick insects can adaptively walk on complex terrains by dynamically adjusting their stepping motion patterns. Inspired by the coupled Matsuoka and resonate-and-fire neuron models, we present a nonlinear oscillation model as the neuromorphic central pattern generator (CPG) for rhythmic stepping pattern generation. This dynamic model can also be used to actuate the motoneurons on a leg joint with adjustable driving frequencies and duty cycles by changing a few of the model parameters while operating such that different stepping patterns can be generated. A novel mixed-signal integrated circuit design of this dynamic model is subsequently implemented, which, although simplified, shares the equivalent output performance in terms of the adjustable frequency and duty cycle. Three identical CPG models being used to drive three joints can make an arthropod leg of three degrees of freedom. With appropriate initial circuit parameter settings, and thus suitable phase lags among joints, the leg is expected to walk on a complex terrain with adaptive steps. The adaptation is associated with the circuit parameters mediated both by the higher level nervous system and the lower level sensory signals. The model is realized using a 0.3- complementary metal-oxide-semiconductor process and the results are reported.

Item Type: Article
Research Areas: A. > School of Science and Technology > Design Engineering and Mathematics
Item ID: 9911
Useful Links:
Depositing User: Zhijun Yang
Date Deposited: 28 Jan 2013 06:45
Last Modified: 13 Oct 2016 14:25
URI: https://eprints.mdx.ac.uk/id/eprint/9911

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