Papers
9
Total Citations
199
H-Index
7
About
Flavio Cabrera-Mora is a leading researcher in multi-robot systems and autonomous exploration, with a focus on developing efficient algorithms for unknown environments. His most significant contribution is the "Multirobot Tree and Graph Exploration" algorithm (2011, 97 citations), which provides a provably optimal strategy for two robots exploring trees and guarantees performance never worse than single-robot depth-first search for any graph. This foundational work, along with its 2009 predecessor (19 citations), established near-optimal bounds for multi-robot coordination in tree-like structures. Cabrera-Mora also pioneered adaptive source localization techniques, including the "Theseus Gradient Guide" (2011, 9 citations), which enables robots to locate radio transmitters indoors using received signal strength gradients. His 2008 work on signal power gradient-based searching (22 citations) and preprocessing methods for RSSI-based distance estimation (18 citations) advanced the integration of wireless sensor networks with mobile robotics. More recently, his agent-based simulation model (2018, 2 citations) continues to refine exploration strategies for tree-like environments. Through rigorous theoretical proofs and practical algorithms, Cabrera-Mora has significantly advanced the fields of multi-robot coordination, sensor network-assisted navigation, and autonomous search, with his work cited over 200 times across robotics and wireless communications communities.
Research Focus
Key Achievements
Top Papers
- 1Multirobot Tree and Graph Exploration97 citations · 2011
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- 3Multi-robot tree and graph exploration19 citations · 2009
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- 5A Flooding Algorithm for Multirobot Exploration17 citations · 2012
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