Coordination for multi-robot exploration and mapping
Abstract
This paper addresses the problem of exploration and mapping of an
unknown environment by multiple robots. The mapping algorithm is an
on-line approach to likelihood maximization that uses hill climbing to
find maps that are maximally consistent with sensor data and odometry.
The exploration algorithm explicitly coordinates the robots. It tries
to maximize overall utility by minimizing the potential for overlap in
information gain amongst the various robots. For both the exploration
and mapping algorithms, most of the computations are distributed. The
techniques have been tested extensively in real-world trials and
simulations. The results demonstrate the performance improvements and
robustness that accrue from our multi-robot approach to
exploration.
Sample citation
Reid G. Simmons,
David Apfelbaum,
Wolfram Burgard,
Dieter Fox,
Mark Moors,
Sebastian Thrun, and
Håkan L. S. Younes. 2000.
Coordination for multi-robot exploration and mapping. In
Proceedings of the Seventeenth National Conference on Artificial Intelligence, 852–858, Austin, Texas. AAAI Press.
Full paper (7 pages, 22 references)
Copyright © 2000, American Association for Artificial Intelligence. All rights reserved.