Zhaoliang Wan
Papers
3
Total Citations
38
H-Index
2
About
Zhaoliang Wan is a robotics researcher whose work bridges underwater automation and intelligent manipulation systems. His primary research areas include marine robotics, autonomous grasping, and visual navigation for robotic systems. Wan’s most impactful contribution is the design of an absorptive-type remotely operated vehicle (ROV) for capturing sea organisms such as sea cucumbers and seashells, a system that integrates vision-based autonomous capture to enhance food economy efficiency and diver safety—a work that has garnered 29 citations. He further advanced robotic manipulation with a novel vacuum cup grasping method that addresses uncertainty in densely cluttered scenes, achieving 8 citations by combining perception data modeling with geometric heuristics. Most recently, Wan has explored diffusion-based imitation learning for visual navigation, introducing a denoising diffusion bridge model that generates action sequences for improved training stability and multimodal distribution handling. His trajectory from practical marine harvesting solutions to cutting-edge learning-based navigation demonstrates a commitment to making robots more autonomous and adaptable in complex, unstructured environments.
Research Focus
Key Achievements
Top Papers
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