Balancing in Dynamic, Unstable Environments Without Direct Feedback of Environment Information

This paper studies the balancing of simple planar bipedal robot models in dynamic, unstable environments such as seesaw, bongoboard, and board on a curved floor. This paper derives output feedback controllers that successfully stabilize seesaw, bongoboard, and curved floor models using only global robot information and with no direct feedback of the dynamic environment and, hence, demonstrates that direct feedback of environment information is not essential for successfully stabilizing the models considered in this paper. This paper presents an optimization to derive stabilizing output feedback controllers that are robust to disturbances on the board. It analyzes the robustness of the derived output feedback controllers to disturbances and parameter uncertainties and compares their performance with similarly derived robust linear quadratic regulator controllers. This paper also presents nonlinear simulation results of the output feedback controllers' successful stabilization of bongoboard, seesaw, and curved floor models.