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Neuromorphic walking gait control.

Susanne Still¹, Klaus Hepp, Rodney J Douglas

¹Department of Information and Computer Sciences, University of Hawaii at Manoa, Honolulu, HI 96822 USA. sstill@hawaii.edu

IEEE Transactions on Neural Networks

|March 29, 2006

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This study introduces a neuromorphic pattern generator chip inspired by biological central pattern generators (CPGs) to control robotic walking gaits. The chip simplifies complex leg coordination into setting a few parameters for efficient, low-power locomotion.

Area of Science:

Robotics
Neuroscience
Integrated Circuit Design

Background:

Controlling quadrupedal robots requires complex inter-leg coordination.
Biological nervous systems utilize central pattern generators (CPGs) for rhythmic motor control, like walking.

Purpose of the Study:

To develop a compact, low-power neuromorphic chip for controlling four-legged robot walking gaits.
To simplify the dynamic control problem of robotic locomotion by mimicking CPG principles.

Main Methods:

Implemented a Very Large Scale Integrated (VLSI) chip with coupled oscillator circuits.
Oscillators mimic simplified motor neuron outputs to generate rhythmic patterns.
Analyzed phase relationships, frequency, and duty cycle of oscillators to determine gait.

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Main Results:

Four coupled oscillators produced appropriate phase relationships for various quadrupedal gaits.
Robot walking behavior was determined by oscillator parameters, controllable via stationary bias voltages.
Analytic expressions derived for gait parameter dependencies.

Conclusions:

The neuromorphic chip effectively reduces complex gait control to setting a few parameters.
This VLSI chip offers a compact and energy-efficient solution for robotic walking gait generation.
The approach bridges principles of biological CPGs with practical robotic applications.