Papers
6
Total Citations
53
H-Index
4
About
Corentin Chauffaut is a robotics and autonomous systems researcher whose work spans aerial robotics, simultaneous localization and mapping (SLAM), and human-agent interaction. His research addresses some of the most challenging problems in autonomous navigation and control, particularly in GPS-denied and dynamically complex environments. Chauffaut's most recognized contribution is his 2017 work on autonomous UAV landing on moving platforms using Model Predictive Control, which has garnered 29 citations and demonstrated high-accuracy tracking capability through a structured three-phase guidance framework — a practically significant advance for real-world drone deployment. His early work on gun-launched micro air vehicles and optical flow-based corridor navigation for quadrotors reflects a foundational interest in agile, resource-constrained aerial platforms operating in confined spaces. More recently, Chauffaut has turned his attention to active visual SLAM, introducing FIT-SLAM, a novel framework integrating Fisher Information and traversability estimation to improve exploration efficiency and localization robustness for ground robots in subterranean and outdoor settings. His 2018 research into human-agent interaction modeling via crowdsourcing further demonstrates a breadth of vision, recognizing the critical role of adaptive behavior in human-robot collaborative missions. Across his career, Chauffaut has consistently pursued autonomy at the intersection of perception, control, and real-world reliability.
Research Focus
Key Achievements
Top Papers
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- 3Human-Agent Interaction Model Learning based on Crowdsourcing6 citations · 2018
- 4The Transition Phase of a Gun-Launched Micro Air Vehicle6 citations · 2012
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