Papers
2
Total Citations
92
H-Index
2
About
Shaolong Yang is a leading researcher in autonomous marine systems, with a primary focus on unmanned surface vehicles (USVs) and underwater robotics. His most influential work, "Cloud-based mission control of USV fleet: Architecture, implementation and experiments" (2020), has garnered 76 citations and established a foundational framework for remote, scalable coordination of multiple autonomous vessels. This contribution directly addresses critical challenges in maritime operations, including fleet management, real-time data integration, and robust communication in dynamic environments. Yang’s research also pushes the boundaries of underwater autonomy, as demonstrated in his recent 2025 paper on "Position-based acoustic visual servo control for docking of autonomous underwater vehicle using deep reinforcement learning," which introduces a novel deep reinforcement learning approach to achieve precise docking—a notoriously difficult task in GPS-denied underwater settings. With 16 citations already, this work signals a growing impact in the field. Yang’s achievements bridge the gap between cloud-based fleet control and intelligent underwater manipulation, offering practical solutions for ocean exploration, environmental monitoring, and defense applications. His work is essential reading for researchers and students interested in the future of autonomous maritime systems.
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