Shape based compliant control with variable coordination centralization on a snake robot
For highly articulated robots, there is a tradeoff between the capability to navigate complex unstructured environments and the high computational cost of coordinating many degrees of freedom. In this work, an approach that we refer to as shape based control helps to balance this trade off using shape functions, geometric abstractions that determine the coupling between multiple degrees of freedom during locomotion. This approach provides a way to intuitively adapt the shape of highly articulated robots using joint level torque feedback control, allowing a robot to compliantly feel its way through unstructured terrain. In this work we specifically focus on compliance in the spatial frequency and temporal phase parameters of a snake like robot's wave like periodic wave like kinematics. We show how varying the spatial frequency within the shape based control architecture allows a single controller to vary the degree to which different degrees of freedom are coupled throughout a mechanism's body, i.e. the controller's degree of centralization. We experimentally find that for a snake like robot locomoting through an irregularly spaced peg array, shape based control results in more effective locomotion when compared to a central pattern generator based approach.
2016 IEEE 55th Conference on Decision and Control (CDC)