Walking trajectory generation for a 3D printing biped robot based on human natural gait and ZMP criteria
Ping Wang, Yabo Wang, Feng Ru
- 发表年份
- 2017
- 引用次数
- 5
摘要
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.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002