Odysseas Kechagias‐Stamatis

City, University of London, Defence Academy of the United Kingdom

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About

Odysseas Kechagias‐Stamatis is a leading researcher in autonomous navigation and space robotics, with a focus on perception, collision avoidance, and multi-agent coordination. His most impactful work, “DeepLO: Multi-projection deep LIDAR odometry for space orbital robotics rendezvous relative navigation” (2020, 27 citations), introduces a novel deep learning framework that fuses multiple LIDAR projections to achieve robust relative navigation during orbital rendezvous—a critical capability for autonomous spacecraft operations. He also developed a bio-inspired visual collision avoidance system for microrobots, detailed in his 2018 paper (17 citations), which mimics the locust’s lobula giant movement detector to enable rapid, reactive obstacle avoidance. More recently, his 2022 work on distributed fuzzy semi-infinite auction-based optimization (2 citations) addresses the challenge of task allocation under uncertainty for cooperative robot teams, using sampling-based approximations to handle imprecise assignments. Kechagias‐Stamatis’s contributions bridge deep learning, bio-inspired sensing, and fuzzy optimization, advancing the reliability and autonomy of robotic systems in both terrestrial and space environments.