Intelligent gait synthesizer for serpentine robots

Abstract

Develops a new gait synthesizer for a snake-like robot in an unstructured changing environment similar to earthquake rubbles. The gait synthesizer, inspired from the GARIC Architecture, is implemented on a simulated navigation of a snake robot. We consider 6 prototypical gaits classified into vertical undulation, lateral undulation, heading changing right/left, flapping right/left. The gait synthesizer is composed of a gait selection network that decides on a combination of prototypical gaits based on a fuzzy controller which is further tuned by a gait evaluation module based on an ANN that learns from prior performances of robot locomotion and acts as an arbiter unit on gait performance. The third module is a stochastic gait modifier, which takes feedback information from the dynamic robotic system and changes the gait based on reinforcement learning.