Dynamically stable gait planning for a humanoid robot to climb sloping surface

Abstract

In this paper, we formulate gait synthesis of humanoid biped locomotion as an optimization problem with consideration of some constraints, e.g. zero-moment point (ZMP) constraints for dynamically stable locomotion, internal forces constraints for smooth transition, geometric constraints for walking on an uneven floor, e.g. sloping surface and etc. In the frame of gait synthesis tied with constraint functions, computational learning methods can be incorporated to further improve the gait. The effectiveness of the proposed dynamically stable gait planning and learning approach for humanoid walking on both even floor and sloping surface has been successfully tested on our humanoid soccer robots named Robo-Erectus, which won first place in the RoboCup 2003 Humanoid League Free Performance competition and got 4 silver awards in the RoboCup Humanoid League 2004.