Motion Planning for Humanoid Robots in Complex Environments Based on Stance Sequence and ZMP Reference Hong Liu a , Qing Sun b Key Lab of Machine Perception and Intelligence Shenzhen Graduate School, Peking University, P.R. China a hongliu@pku.edu.cn, b sunqing@pku.edu.cn Keywords: Footstep Planning, Motion Planning, Robot and Mechanics Abstract. It is a great challenge to plan motion for humanoid robots in complex environments especially when the terrain is cluttered and discrete. To address this problem, a novel method is proposed in this paper by planning the gait according to the stance sequence and ZMP (Zero Moment Point) reference. It consists of two components: an adaptive footstep planner and a walking pattern generator. The adaptive footstep planner can generate the stance path according to the walking rules and adjust the orientation of body relevantly. As the footstep locations are determined, Linear Inverted Pendulum Model (LIPM) is used to generate the walking pattern with a moving ZMP reference. As demonstrated in experiments on the humanoid robot HOAP-2, our method can successfully plan footstep trajectories as well as generate the stable and natural-looking gait in typical cluttered and discrete environments. Introduction Humanoid robotics has been an intensive research area during the last decade. The popularity of humanoid robots is largely owing to their higher flexibility of action and better mobility. In recent years, various methods of planning the motion for humanoid robot in complex environment have appeared [1, 2]. However, there is few work of humanoid robot walking on discrete and cluttered environment, where the robot has fewer choices for the next step and needs more precise planning. Fig. 1 gives a typical example of discrete and cluttered environments—“Plum Blossom Piles”, which is a platform to practice Chinese Kung Fu. It is important to notice that there are many tasks which require the robot to deal with these terrains, such as rescuing the victims in the earthquake, crossing a danger area, walking over the puddles, etc. Moreover, most of these tasks are not safe for human, which is a potential field for humanoid robots. Fig.1: The plum blossom piles Traditional footstep planning method relies on footstep transition model [3]. So the planning result is guided by the predetermined footstep model and cannot adapt to complex environments well. In