Stochastic optimization of bipedal walking using gyro feedback and phase resetting

We present a method to optimize the walking pattern of a humanoid robot for forward speed using suitable metaheuristics. Our starting point is a hand-tuned open-loop gait that we enhance with two feedback control mechanisms. First, we employ a P-controller that regulates the foot angle in order to reduce angular velocity of the robot´s body. Second, we introduce a phase resetting mechanism that starts the next step at the moment of foot contact. Using a physics-based simulation, we demonstrate that such feedback control is essential for achieving fast and robust locomotion.