Prescription of rhythmic patterns for legged locomotion

As the engine behind many life phenomena, motor information generated by the central nervous system (CNS) 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 (DOF) with adjustable oscillatory frequencies and duty cycles. An OBBs 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

Sensor-driven neuromorphic walking leg control

We present a simple neuromorphic central pattern generators (CPG) circuit module, which is essentially a pair of coupled oscillators, to actuate a joint on a leg. This novel, reconfigurable CPG module is able to generate different motor patterns of different frequencies or duty cycles, simply by changing a few of circuit parameters. Three CPG modules, corresponding to three joints, can make an arthropod leg of three degrees of freedom (DOFs). With appropriate 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 by external commands or sensory signals. Simulation results for the circuitry, designed using a 0.35 mum process, are reported