Snakes on an inclined plane: Learning an adaptive sidewinding motion for changing slopes

Abstract

Sidewinding is an efficient gait adopted by biological and robotic snakes for locomoting on various terrains. The mechanics of this motion on flat ground and steady state terrains have been thoroughly investigated, while its capability to adapt to changing environments is not as well studied. We demonstrate the capability of a snake robot to automatically adjust gait parameters to optimally move up and down slopes of varying angle. This capability is achieved by three components. First, an efficient offline learning algorithm finds a policy mapping the estimated slope angle to the optimal gait parameters. Next, a robust online state estimation technique infers the local terrain characteristics. Finally, the precomputed policy is consulted online to select the optimal gait parameters for this slope. The efficacy of this approach is verified by robot experiments.