Optimized Whole-body Motion Control for Wheeled Humanoid Robots

In this paper, the whole-body motion control of a dynamically-stable two-wheeled humanoid robot is investigated. With feedback linearization as a control law cooperating with a stochastic optimization
technique called particle swarm optimization (PSO) to search for an optimal set of certain unknown parameters, an optimal robot motion can be realized according to a pre-fined performance index. The main contribution of this work is our first success on implementing the proposed control strategy on the actual physical system, Golem Krang, a novel two-wheeled humanoid robot developed at Georgia Tech. The experiments are demonstrated by two primitive motions, standing from the ground and deceleration.