Thibaud Duhautbout
Papers
1
Total Citations
12
H-Index
1
About
Thibaud Duhautbout is a robotics researcher whose work centers on advancing multi-robot perception and mapping in three-dimensional environments. His most influential contribution, "Distributed 3D TSDF Manifold Mapping for Multi-Robot Systems" (2019), introduces a novel framework for collaborative, real-time 3D reconstruction using truncated signed distance functions (TSDF) on manifolds. This approach enables multiple robots to efficiently fuse their individual sensor data into a shared, consistent map without centralized processing, addressing critical challenges in scalability and communication bandwidth for swarm robotics. Garnering 12 citations, this paper has been recognized by the international robotics community for its practical impact on autonomous exploration, search-and-rescue, and industrial inspection tasks. Duhautbout’s work stands out for its elegant integration of manifold theory with distributed systems, offering a mathematically grounded solution to the problem of maintaining global map coherence across heterogeneous robot teams. His research continues to influence the design of resilient, decentralized mapping algorithms, making him a notable contributor to the field of multi-robot coordination and 3D perception.
Research Focus
Key Achievements
Top Papers
- 1Distributed 3D TSDF Manifold Mapping for Multi-Robot Systems12 citations · 2019