Papers
6
Total Citations
346
H-Index
4
About
Quentin Leboutet’s research lies at the intersection of robot skin, whole-body compliance, and inertial parameter identification—fields critical to making robots safer and more adaptive. His most cited work, “A Comprehensive Realization of Robot Skin” (192 citations), delivers a holistic engineering framework for multimodal artificial skin, enabling large-area tactile sensing with human-like capabilities. Building on this, his tactile-based control methods (40+ citations) allow mobile manipulators to achieve whole-body compliance through hierarchical force propagation, responding intelligently to multi-contact interactions. Leboutet also made a foundational contribution to robot dynamics with his survey on inertial parameter identification (95 citations), where he introduced BIRDy, an open-source Matlab toolbox that standardizes benchmarking across the field. His recent work extends into autonomous navigation: IN-Sight (2024) tackles interactive path planning in dynamic environments, while OpenBot-Fleet (2024) leverages smartphones and cloud infrastructure for collective robot learning at scale. By bridging tactile sensing, dynamics identification, and cloud-based autonomy, Leboutet’s research provides practical tools and theoretical insights that empower robots to perceive, comply, and navigate in unstructured human environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Inertial Parameter Identification in Robotics: A Survey95 citations · 2021
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- 4
- 5IN-Sight: Interactive Navigation through Sight4 citations · 2024
- 6OpenBot-Fleet: A System for Collective Learning with Real Robots1 citations · 2024