Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6866045 | Neurocomputing | 2015 | 8 Pages |
Abstract
We propose a simple yet efficient way of coordinating multiple homogeneous robots in the exploration of unknown environments. A guided probabilistic exploration of an unknown environment is achieved via combining random movement with pheromone-based stigmergic guidance. The emergent strategy is shown to provide a scalable solution to multi-robot coordination for the area exploration task, with a faster than linear speed-up with the addition of new robots. We utilize an approach to evaluating the desired exploration behavior that emphasizes “surveying” rather than “scanning” the environment. We analyze the emergent exploration strategies and demonstrate their effectiveness in higher complexity environments.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Tüze Kuyucu, Ivan Tanev, Katsunori Shimohara,