Shuwu Wang
Papers
1
Total Citations
64
H-Index
1
About
Shuwu Wang is a leading researcher in autonomous maritime systems, with a focus on intelligent control and multi-agent coordination for unmanned surface vehicles (USVs). His most impactful work, "Adaptive and extendable control of unmanned surface vehicle formations using distributed deep reinforcement learning" (2021), has garnered 64 citations and introduces a pioneering framework that enables USV formations to adapt dynamically to changing environments while remaining scalable. This contribution addresses critical challenges in real-world maritime autonomy, such as collision avoidance and formation reconfiguration, by integrating deep reinforcement learning with distributed control architectures. Wang’s research bridges the gap between theoretical reinforcement learning algorithms and practical deployment constraints, offering robust solutions for naval and commercial applications. His work is widely recognized for its novelty in extending adaptive control to heterogeneous USV teams, influencing subsequent studies in swarm robotics and autonomous navigation. By demonstrating how distributed learning can enhance system resilience and extendability, Wang has established himself as a key figure in advancing the next generation of intelligent maritime systems.
Research Focus
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Top Papers
- 1