Flat-Foot Dynamic Walking via Human-Inspired Controller Design

This thesis describes a torque control scheme unifying feedback PD control and feed-forward impedance control to realize human-inspired walking on a novel planar footed bipedal robot: AMBER2. It starts with high fidelity modeling of the robot including nonlinear dynamics, motor model, and impact dynamics. Human data is then used by an optimization algorithm to produce a human-like walking gait that can be implemented on the robot, which is represented in the form of canonical walking functions. To realize the bipedal walking, first a PD controller is utilized to track the optimized trajectory. Next, impedance control parameters are estimated from the experimental data of a successful walking with AMBER2. Finally, the unified PD, impedance torque control law is experimentally realized on the bipedal robot AMBER2. Through the evidence of sustainable and unsupported walking achieved on AMBER2 showing high consistency with the simulated walking gait, the feasibility of AMBER2 walking scheme will be verified.