About

Frederick Ducatelle is a pioneering researcher whose work spans swarm robotics, multi-robot systems, and computer vision-based human-robot interaction. His contributions have fundamentally shaped how scientists design, simulate, and study collective robotic behavior, earning him well over 1,500 citations across his most influential works. Ducatelle is perhaps best known for his pivotal role in developing ARGoS, a modular, parallel, multi-engine simulator for heterogeneous swarm robotics systems, which has become an indispensable tool in the field with nearly 700 combined citations. His work on the Swarmanoid project (408 citations) introduced a groundbreaking framework for studying heterogeneous robotic swarms, exploring how decentralized, locally communicating robots can produce sophisticated emergent global behaviors. This research demonstrated remarkable potential for flexibility and robustness in swarm systems. His investigations into cooperative navigation and self-organization in robotic swarms revealed how robots can guide one another through wireless communication networks, advancing practical deployment of swarm systems. Additionally, his foray into deep learning produced a highly cited study (648 citations) on convolutional neural networks for real-time hand gesture recognition, bridging computer vision with human-robot interaction. Together, these contributions establish Ducatelle as a versatile and influential figure in autonomous robotics research.

Research Focus

Key Achievements

12
H-Index
16
Papers
2,135
Total Citations
133
Avg Citations/Paper
🏆 Most Cited Paper
Max-pooling convolutional neural networks for vision-based hand gesture recognition
648 citations · 2011
📈 Most Prolific Year: 2011 (6 Papers)
🤝 Key Collaborators: 44
🏛 Institutions: Università della Svizzera italiana, University of Applied Sciences and Arts of Southern Switzerland, Dalle Molle Institute for Artificial Intelligence Research

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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