Yuheng Chen
Papers
3
Total Citations
37
H-Index
3
About
Yuheng Chen is a rising researcher in the field of autonomous underwater robotics, with a focused expertise in the dynamic modeling, learning-based control, and path planning of remotely operated vehicles (ROVs) for deep-sea mining applications. Chen’s major contributions lie in developing intelligent control frameworks that enable ROV-based mining vehicles to operate reliably in the harsh, uncertain conditions of the deep ocean. Notably, their 2024 paper on dynamic modeling and learning-based path tracking control has already garnered 25 citations, establishing a foundational approach for precise vehicle navigation. Building on this, Chen’s 2025 work on cooperative control addresses the challenge of managing uncertain nonlinear dynamics through learned models, while their obstacle avoidance strategy introduces a learning-based method for safe autonomous navigation in complex underwater terrains. Though early in their career, Chen’s cumulative work—totaling over 37 citations—is shaping the next generation of autonomous deep-sea mining systems, with potential applications in resource extraction and environmental monitoring. Their research is particularly valuable for students and engineers interested in the intersection of reinforcement learning, nonlinear control, and marine robotics.
Research Focus
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Top Papers
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