This paper presents a novel hardware-efficient central pattern generator (CPG) model to realize a bio-inspired gait of a hexapod robot. The CPG model consists of a network of cellular automaton (CA) oscillators; thus, it can be implemented as a network of sequential logic circuits. Detailed analyses of nonlinear oscillation dynamics show that the oscillator that is driven by multiple asynchronous clocks is more suitable to realize the gait of the robot than an oscillator that is driven by a single clock or multiple synchronous clocks. Moreover, detailed analyses of nonlinear network dynamics show that the clocks among the CA oscillators should be asynchronous to appropriately realize the gait. Using the analyses, systematic procedures to design the CPG model are proposed. The proposed CPG model is implemented in a field programmable gate array (FPGA); our experiments validate that the CPG model implemented in an FPGA can realize the bio-inspired gait of a hardware robot. Further, we show that the proposed CPG model utilizes fewer circuit elements and lower power than a conventional CPG model. INDEX TERMS Asynchronous Cellular Automaton. Central Pattern Generator (CPG). Field Programmable Gate Array (FPGA). Hexapod Robot. Nonlinear dynamics. Synchronization.

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In this paper, we present a cochlea model whose nonlinear dynamics are described by an asynchronous cellular automaton. Our proposed model is demonstrated to enable the reproduction of twotone distortion products. The proposed model is implemented on a field-programmable gate array (FPGA). It is subsequently demonstrated that our proposed model can be implemented using fewer hardware resources than a conventional cochlea model, which is a Hopf-type cochlea model, implemented on a digital signal processor performing a numerical integration.

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