ACHIEVING ENERGY-EFFICIENT BIPEDAL WALKING TRAJECTORY THROUGH GA-BASED OPTIMIZATION OF KEY PARAMETERS
Van-Huan Dau, Chee–Meng Chew, Aun-Neow Poo
- 发表年份
- 2009
- 引用次数
- 28
摘要
This paper proposes a method of energy-efficient trajectory planning for bipedal walking robots. In this study, we plan hip and foot trajectories in Cartesian space using polynomial interpolation. The seven key parameters which define the hip and foot trajectories are optimized by genetic algorithm (GA). Since the hip trajectory is crucial to the stability and walking performance of bipedal robot, we introduce a way to increase hip trajectory's variation by extending the order of the interpolated polynomial and using a set of key parameters. To ensure stable walking motion, we employ the zero-moment-point (ZMP) as the stability criterion. The effectiveness of our proposed method is verified by two simulation examples (flat terrain walking and slope walking) of a humanoid robot named NUSBIP-II.
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