Paper
30 October 1996 Adaptive leg coordination with a biologically inspired neurocontroller
Grant Braught, Stelios C.A. Thomopoulos
Author Affiliations +
Abstract
Natural selection is responsible for the creation of robust and adaptive control systems. Nature's control systems are created only from primitive building blocks. Using insect neurophysiology as a guide, a neural architecture for leg coordination in a hexapod robot has been developed. Reflex chains and sensory feedback mechanisms from various insects and crustacea form the basis of a pattern generator for intra-leg coordination. The pattern generator contains neural oscillators which learn from sensory feedback to produce stepping patterns. Using sensory feedback as the source of learning information allows the pattern generator to adapt to changes in the leg dynamics due to internal or external causes. A coupling between six of the single leg pattern generators is used to produce the inter-leg coordination necessary to establish stable gaits.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Grant Braught and Stelios C.A. Thomopoulos "Adaptive leg coordination with a biologically inspired neurocontroller", Proc. SPIE 2905, Sensor Fusion and Distributed Robotic Agents, (30 October 1996); https://doi.org/10.1117/12.256335
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Cited by 1 scholarly publication.
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KEYWORDS
Neurons

Sensors

Linear filtering

Position sensors

Gait analysis

Control systems

Device simulation

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