Economic model predictive control for obstacle-aided snake robot locomotion
Evan Müller, Philipp N. Köhler, Kristin Y. Pettersen, Frank Allgöwer
- 发表年份
- 2020
- 引用次数
- 7
摘要
This paper studies the application of economic model predictive control (MPC) to snake robot locomotion. The proposed MPC algorithm integrates the gait pattern creation into the closed loop by maximizing the forward snake velocity. We consider both purely planar locomotion as well as obstacle-aided locomotion. A compliant obstacle-snake contact model is introduced, rendering the interaction dynamics considered in the optimal control problem smooth. We illustrate the efficacy of the scheme by numerical simulations. The emerging gait patterns are undulatory and can make simultaneous use of anisotropic ground friction and obstacles.
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