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Yogang Singh is a leading researcher in autonomous maritime robotics, with a primary focus on the guidance, navigation, and control of Unmanned Surface Vehicles (USVs). His work centers on solving critical challenges in multi-robot coordination, particularly through the development of hybrid frameworks that integrate formation control and cooperative motion planning. Singh’s most impactful contribution is his 2020 paper proposing a novel double-layered hybrid framework for USV swarms in practical maritime environments, which has garnered 49 citations and stands as a cornerstone in the field. He has also advanced efficient optimal path planning for USVs navigating dynamic obstacle fields, and more recently, he has pioneered simulation-based approaches using the Marine Robotics Unity Simulator to enable high-fidelity testing of autonomous navigation systems, addressing the critical gap in sea trial availability. With a cumulative citation count exceeding 55, Singh’s work directly supports the deployment of USVs for coastal monitoring and oceanographic applications, making him a key figure in bridging theoretical multi-robot motion planning with real-world maritime autonomy.