Neuro-control using temporal dynamics for robot locomotion

A neural controller for an autonomous walking machine called the Micro-Rover is presented. Dynamic properties of real neurons were incorporated within the neural model in the form of delayed excitation. The pattern generation capability of networks of biological neurons were studied in order to choose an appropriate gait controller for the Micro-Rover. A four-phasic network with recurrent inhibition was found to be suitable for generating the locomotion rhythm. Sensory modulation of the locomotion rhythm takes place within local networks that coordinate leg and frame actuation. A simple reflex circuit enables the Micro-Rover to avoid obstacles. The networks were developed and tested numerically, and work is currently underway to implement the controller on the Micro-Rover