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About

Ian Higgins is a leading robotics researcher whose work tackles some of the most challenging environments for autonomous systems: from underground tunnels to crowded skies. His primary research areas span resilient subterranean exploration, social robot navigation, and safe manned-unmanned aircraft teaming. Higgins made major contributions to the DARPA Subterranean Challenge, where his team demonstrated a comprehensive approach using roving and flying robots to overcome mobility, communication, and navigation barriers in GPS-denied environments—work that has garnered over 50 citations. He also developed the SubT-MRS dataset, a pioneering resource pushing SLAM algorithms toward all-weather resilience, with 46 citations since its 2024 release. For aerial systems, Higgins introduced SoRTS (Social Robot Tree Search), a learned tree search algorithm enabling long-horizon, socially-aware navigation in shared airspace. His work on close-proximity manned-unmanned aircraft operations addresses critical safety challenges for future airspace integration. With over 100 total citations across his most-cited papers, Higgins is shaping the future of autonomous exploration and navigation in the world’s most demanding environments.