Charles Champagne Cossette
Papers
9
Total Citations
124
H-Index
5
About
Charles Champagne Cossette is a leading researcher in multi-robot systems, specializing in relative pose estimation, ultra-wideband (UWB) localization, and decentralized state estimation for GPS-denied environments. His work addresses fundamental challenges in collaborative robotics, particularly how teams of robots can accurately determine each other’s positions and orientations using only inter-agent range measurements. His most influential paper, “Relative Position Estimation in Multi-Agent Systems Using Attitude-Coupled Range Measurements” (60 citations), pioneered methods for leveraging UWB radio signals to achieve precise relative positioning without external infrastructure. Cossette’s contributions extend to optimal formation design for pose estimation, UWB calibration and uncertainty characterization, and novel approaches to magnetic navigation for loop closure detection. He developed the open-source Python package *navlie* for state estimation on Lie groups, enabling rapid prototyping of navigation algorithms. His work on passive UWB transceivers and decentralized estimation using pseudomeasurements has advanced the scalability of multi-robot localization. With over 120 total citations and a growing portfolio of high-impact publications, Cossette is shaping the future of autonomous robotic teams operating in challenging, infrastructure-free environments.
Research Focus
Key Achievements
Top Papers
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- 7MILUV: A Multi-UAV Indoor Localization dataset with UWB and Vision2 citations · 2026
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- 9navlie: A Python Package for State Estimation on Lie Groups2 citations · 2023