Thomas A. DeCoster
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1
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1
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About
Thomas A. DeCoster is a leading researcher in multi-agent robotic systems, with a focus on relative pose estimation and state estimation in GPS-denied environments. His work addresses the critical challenge of enabling collaborative autonomy among robots when global positioning infrastructure is unavailable. DeCoster’s major contribution lies in developing novel filtering techniques, such as the unscented particle filter, to fuse Ultra-Wideband (UWB) range measurements with visual-inertial odometry (VIO) for real-time relative pose estimation. This approach overcomes fundamental observability issues in single-range scenarios, allowing agents to infer their relative positions and orientations even during unobservable motion—a breakthrough for applications like swarm robotics, search-and-rescue, and underground exploration. His most-cited paper, “Where are You? Unscented Particle Filter for Single Range Relative Pose Estimation in Unobservable Motion Using UWB and VIO” (2024), has already garnered attention for its practical impact, with 1 citation in its early stages. DeCoster’s work is notable for bridging theoretical estimation challenges with real-world deployment, making him a rising figure in the field of multi-agent coordination and sensor fusion.
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Top Papers
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