Title :
A practical, decision-theoretic approach to multi-robot mapping and exploration
Author :
KO, Jonathan ; Stewart, Benjamin ; Fox, Dieter ; Konolige, Kurt ; Limketkai, Benson
Author_Institution :
Comput. Sci. & Eng., Washington Univ., Seattle, WA, USA
Abstract :
An important assumption underlying virtually all approaches to multi-robot exploration is prior knowledge about their relative locations. This is due to the fact that robots need to merge their maps so as to coordinate their exploration strategies. The key step in map merging is to estimate the relative locations of the individual robots. This paper presents a novel approach to multi-robot map merging under global uncertainty about the robot´s relative locations. Our approach uses an adapted version of particle filters to estimate the position of one robot in the other robot´s partial map. The risk of false-positive map matches is avoided by verifying match hypotheses using a rendezvous approach. We show how to seamlessly integrate this approach into a decision-theoretic multi-robot coordination strategy. The experiments show that our sample-based technique can reliably find good hypotheses for map matches. Furthermore, we present results obtained with two robots successfully merging their maps using the decision-theoretic rendezvous strategy.
Keywords :
decision theory; merging; mobile robots; multi-robot systems; decision-theoretic multi-robot coordination strategy; decision-theoretic rendezvous strategy; false positive map matches; global uncertainty; map merging problem; match hypotheses; multi-robot exploration; multi-robot mapping; partial filter; seamless integration; Artificial intelligence; Computer science; Knowledge engineering; Merging; Particle filters; Robot kinematics; Robustness; Uncertainty;
Conference_Titel :
Intelligent Robots and Systems, 2003. (IROS 2003). Proceedings. 2003 IEEE/RSJ International Conference on
Print_ISBN :
0-7803-7860-1
DOI :
10.1109/IROS.2003.1249654