Bipedal Robotic Running on Stochastic Discrete Terrain
Ayush Agrawal, Koushil Sreenath
- 发表年份
- 2019
- 引用次数
- 6
摘要
To navigate over discrete terrain with large displacements in the stepping locations, bipedal robots have to be able to perform agile and dynamic maneuvers such as jumping or running while also satisfying strict constraints on foot placement and ground contact forces. In this paper, we analyze the problem of bipedal running over stochastically varying discrete terrain with large changes in step lengths. Specifically, our method is based on designing a library of running gaits that are two-step-periodic. We illustrate the capabilities of the proposed controller through numerical simulations of a five link underactuated robot RABBIT, running over discrete terrain with step lengths that vary between 0.6m and 1.2m. This is about 1.5 times the robot's leg lengths and twice the step length that could have been achieved by walking.
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