Abstract

This paper proposes a CPG-based control architecture using a frequency-adaptive oscillator for undulatory locomotion of snake-like robots. The control architecture consists of a network of neural oscillators that generates desired oscillatory output signals with specific phase lags. A key feature of the proposed architecture is a self-adaptation process that modulates the parameters of the CPG to adapt the motion of the robot to varying coefficients of body-ground friction. This process is based on the frequency-adaptation rule of the oscillator that is designed to learn the periodicity of sensory feedback signals. It has an important meaning of establishing a closed-loop CPG much more robust against environmental and/or system parameter changes. We verify the validity of the proposed locomotion control system employing a simulated snake-like robot moving over terrains with different friction coefficients with a constant velocity.

How Multibody Dynamics Simulation Technology is Used

A proposed CPG-based control architecture enhanced performance of lateral undulatory locomotion of snake-like robots. This method was verified by running RecurDyn simulations over a variety of different ground friction conditions. The lateral undulatory locomotion was proven to be an effective method of locomotion for snake-like robots.

Get This Paper

• http://link.springer.com/article/10.1007/s11370-009-0049-4

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