Alan Papalia

Massachusetts Institute of Technology, Woods Hole Oceanographic Institution

Papers

Total Citations

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About

Alan Papalia is a leading researcher in robotics and autonomous systems, specializing in state estimation, simultaneous localization and mapping (SLAM), and multi-robot coordination. His major contributions center on **range-aided SLAM (RA-SLAM)**, where he has pioneered certifiably optimal and computationally efficient solutions for robotic navigation using point-to-point distance sensors. His 2024 paper, "Certifiably Correct Range-Aided SLAM" (14 citations), introduced the first algorithm to guarantee optimal solutions in RA-SLAM, a critical advancement for reliable underwater and GPS-denied navigation. Papalia also developed **SCORE** (2023, 8 citations), a second-order conic initialization technique that dramatically improves RA-SLAM accuracy. In multi-robot systems, his "Prioritized Planning for Cooperative Range-Only Localization" (2022, 14 citations) provides a novel path-planning algorithm to minimize localization error in robot networks. Extending his work to human-robot teams, Papalia's 2022 paper on loosely-coupled human-AUV operations (2 citations) demonstrates practical algorithms for diver navigation without ocean infrastructure. With over 38 total citations across his most-cited works, Papalia's research is foundational for certifiable, scalable, and cooperative robotic navigation in challenging environments.