Walking pattern generation involving 3D waist motion for a biped humanoid robot

Abstract

In this paper, a method for generating a natural human-like walking pattern of a humanoid robot is proposed. Inspired by biomechanical studies on human walking, we model the walking pattern of the robot with continuous and differentiable mathematical functions. The proposed walking pattern involves three-dimensional waist motion of the robot instead of restricting the waist motion to a two-dimensional planar surface. Considering the real environment includes not only unevenness but also some degree of inclination that may cause the walking to be unstable, this paper also presents a method of controlling the body posture of the humanoid robot. The posture controller utilizing ankle joints is based on sensory feedback and modifies the reference trajectories in real time in order to stabilize the robot. We have implemented the proposed walking pattern and control method on the humanoid robot NAO. Dynamic walking experiments have verified that the proposed scheme improves the walking stability of the robot.

A 3D Non-Stationary Cluster Channel Model for Human Activity Recognition

“…respectively, where the parameter H foot represents the maximum displacement of the foot while walking along the z-axis. The ankle models presented in (C.22)-(C.25) were inspired by the ankle model of humanoid robotics provided in [16]. Next, we define the displacements of the right and left wrist in the x-direction as follows where the parameter z w denotes the maximum vertical displacement of the wrists.…”