Robot exploration with combinatorial auctions
M. Berhault, Huili Huang, Pınar Keskinocak, Sven Koenig, Wedad Elmaghraby, Paul M. Griffin, Anton J. Kleywegt
- Year
- 2004
- Citations
- 182
Abstract
We study how to coordinate a team of mobile robots to visit a number of given targets in a partially unknown terrain. Robotics researchers have studied single-item auctions to perform this exploration task but these do not make synergies between the targets into account. We therefore design combinatorial auctions, propose different combinatorial bidding strategies and compare their performance with each other, as well as to single item auctions and an optimal centralized mechanism. Our computational results in teambots, a multi-robot simulator, indicate that combinatorial auctions generally lead to significantly superior team performance than single-item auctions, and generate very good results compared to an optimal centralized mechanism.
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