Walking trajectory generation for a 3D printing biped robot based on human natural gait and ZMP criteria

Abstract

With development of 3D printing technology, making a customized robot is more fast and easy. In order to adapted various walking patterns for the customized biped robot, mimic human gait is one of the solutions. In this paper, human natural gait is firstly obtained by video system. The human body is modeled to use kinematic equations to find the joint angle from the captured trajectory. However, direct application of those captured joint angle data into the robot presents unnatural and poor balance. An improved walking trajectory algorithm is proposed based on the human natural gait and ZMP (zero moment point) criteria. The generated new gait trajectories are tested on the simulation model to get the stability of each joint movement and generate gait trajectory of the robot. Adapted walking pattern is successfully applied on the 3D printing biped robot.