Task allocation in robotic swarms: new methods and comparisons
Frederic Ducatelle, A. Foerster, Gianni A. Di, Luca Maria Gambardella
- 发表年份
- 2009
- 引用次数
- 8
摘要
We study a situation where a swarm of robots is deployed to resolve multiple concurrent tasks in a confined arena. The tasks are announced by dedicated robots at different locations in the arena. Each task requires a certain number of robots to attend to it simultaneously. We address the problem of task allocation: how can the robots of the swarm assign themselves to one of the announced tasks in a distributed and efficient way? We propose two novel methods: one relies on simple reactive mechanisms that are based on interaction through light signals, while the other uses a more advanced gossip-based communication scheme to announce task requirements among the robots. We evaluate both methods, and compare their performance. We investigate specifically the scalability and robustness of both methods, in order to understand their relative usefulness in different swarm deployment conditions.
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