A compositional framework for programming stochastically interacting robots
Nils Napp, Eric Klavins
- 发表年份
- 2011
- 引用次数
- 22
摘要
Large collections of simple, interacting robots can be difficult to program due to issues of concurrency and intermittent, probabilistic failures. Here, we present Guarded Command Programming with Rates , a formal framework for programming such multi-robot systems. Within this framework, we model robot behavior as a stochastic process and express concurrency and program composition using simple operations. In particular, we show how composition and other operations on programs can be used to specify increasingly complex behaviors of multi-robot systems and how stochasticity can be used to create programs that can tolerate failure of individual robots. Finally, we demonstrate our approach by encoding algorithms for routing parts in an abstract model of the Stochastic Factory Floor testbed (Galloway et al. 2010).
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