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Prescription of rhythmic patterns for legged locomotion

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Abstract

As the engine behind many life phenomena, motor information generated by the central nervous system plays a critical role in the activities of all animals. In this work, a novel, macroscopic and model-independent approach is presented for creating different patterns of coupled neural oscillations observed in biological central pattern generators (CPG) during the control of legged locomotion. Based on a simple distributed state machine, which consists of two nodes sharing pre-defined number of resources, the concept of oscillatory building blocks (OBBs) is summarised for the production of elaborated rhythmic patterns. Various types of OBBs can be designed to construct a motion joint of one degree of freedom with adjustable oscillatory frequencies and duty cycles. An OBB network can thus be potentially built to generate a full range of locomotion patterns of a legged animal with controlled transitions between different rhythmic patterns. It is shown that gait pattern transition can be achieved by simply changing a single parameter of an OBB module. Essentially, this simple mechanism allows for the consolidation of a methodology for the construction of artificial CPG architectures behaving as an asymmetric Hopfield neural network. Moreover, the proposed CPG model introduced here is amenable to analogue and/or digital circuit integration.

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Acknowledgments

This research has been supported in part by a British Biotechnology and Biological Sciences Research Council (BBSRC) Grant BBS/B/07217, an Engineering and Physical Sciences Research Council (EPSRC) Grant EP/E063322/1, and two Chinese National Science Foundation (NSFC) Grants 60673102 and 61103185. The MATLAB–Simulink program is available upon request.

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Yang, Z., Zhang, D., Rocha, M.V. et al. Prescription of rhythmic patterns for legged locomotion. Neural Comput & Applic 28, 3587–3601 (2017). https://doi.org/10.1007/s00521-016-2237-4

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