Emanuele Caselli
Piaggio Aerospace (Italy), IMT School for Advanced Studies Lucca
Papers
3
Total Citations
156
H-Index
3
About
Emanuele Caselli is a leading researcher in the field of bio-inspired robotics and autonomous gas/odor source localization. His work focuses on developing algorithms that enable robots to detect and pinpoint chemical sources in challenging indoor environments where airflow is minimal or nonexistent—a problem critical for applications in environmental monitoring, hazardous material detection, and search-and-rescue operations. Caselli’s most influential contribution is the SPIRAL algorithm (125 citations), a biologically-inspired approach that mimics the foraging behavior of insects to efficiently locate gas sources. He has also pioneered multi-robot strategies, including the Explorative Particle Swarm Optimization method (15 citations), which uses a swarm of robots to collaboratively explore and localize sources. Additionally, his work on Bayesian occupancy grid mapping (16 citations) introduced a probabilistic framework for localizing multiple gas sources simultaneously, significantly advancing the state of the art. Caselli’s research has been instrumental in bridging the gap between biological sensing principles and practical robotic systems, making him a key figure in the development of autonomous chemical sensing technologies.
Research Focus
Key Achievements
Top Papers
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