In this paper we describe a roadmap-based approach for a multi-agent search strategy to clear a building or multi-story environment. This approach utilizes an encoding of the environment in the form of a graph (roadmap) that is used to encode feasible paths through the environment. The roadmap is partitioned into regions, e.g., one per level, and we design region-based search strategies to cover and clear the environment. We can provide certain guarantees within this roadmap-based framework on coverage and the number of agents needed. Our approach can handle complex and realistic environments where many approaches are restricted to simple 2D environments. © 2011 Springer-Verlag.
CITATION STYLE
Rodriguez, S., & Amato, N. M. (2011). Roadmap-based level clearing of buildings. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7060 LNCS, pp. 340–352). https://doi.org/10.1007/978-3-642-25090-3_29
Mendeley helps you to discover research relevant for your work.