Stereo vision and terrain modeling for quadruped robots
J. Zico Kolter, Youngjun Kim, Andrew Y. Ng
- 发表年份
- 2009
- 引用次数
- 73
摘要
Legged robots offer the potential to navigate highly challenging terrain, and there has recently been much progress in this area. However, a great deal of this recent work has operated under the assumption that either the robot has complete knowledge of its environment or that its environment is suitably regular so as to be navigated with only minimal perception, an unrealistic assumption in many real-world domains. In this paper we present an integrated perception and control system for a quadruped robot that allows it to perceive and traverse previously unseen, rugged terrain that includes large, irregular obstacles. A key element of the system is a novel terrain modeling algorithm, used for filling in the occluded models resulting from on-board vision systems. We apply our approach to the LittleDog robot, and show that it allows the robot to walk over challenging terrain using only on-board perception.
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