Online ZMP sampling search for biped walking planning

In this paper, we present a new method that uses random search for online planning of biped walking, given a feasible footstep plan. The Linear Inverted Pendulum dynamic model and the Zero Moment Point concept are employed to solve the walking problem. We consider walk planning as the choice of a sequence of ZMPs leading to a stable walk that satisfies all the dynamic and mechanical constraints of the robot. We contribute a novel online sampling algorithm to efficiently search for such ZMP sequence. We demonstrate the effectiveness of the algorithm by successful combined walking tasks in a faithful simulation of a full-body humanoid robot.