A Universal Biped Walking Generator for Complex Environments with Pattern Feasibility Checking

In this paper, we propose a universal biped walking generator that can plan smooth and flexible walking motions in complex environments, including stairs, slopes, and obstacles. In addition to generating collision-free patterns while keeping the balance of the robot, this generator also checks whether the patterns are achievable for the robot. Aiming at this goal, we introduce a simplified walking method to specify the complete biped motions with the unit of a walking step, instead of a time step of the robot’s working time used in usual methods. The zero moment point sampling search is also proposed as an efficient method to determine the walking solution for a feasible footstep plan while simultaneously considering dynamic balance and feasibility. Furthermore, another sampling-based algorithm is proposed to revise unfeasible footstep plans to feasible ones. The feasibility and the efficiency of our proposed approach are demonstrated by experiments on simulated and real Nao robots.