Market-Driven Multi-Robot Exploration
Robert Zlot, Anthony Stentz, M. Bernardine Dias, Scott Thayer
- Year
- 2002
- Citations
- 67
Abstract
For many real-world applications, autonomous robots must execute complex tasks in unknown or partially known unstructured environments. This work presents a novel approach to efficient multi-robot mapping and exploration which exploits a market architecture in order to maximize information gain while minimizing incurred costs. This system is reliable and robust in that it can accommodate dynamic introduction and loss of team members in addition to communication interruptions and failures. Results showing the capabilities of our system on a team of exploring autonomous robots are also given.
Keywords
Related papers
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