Papers
3
Total Citations
20
H-Index
2
About
Shuai Gan is a rising researcher in intelligent robotic assembly and manipulation, with a focus on overcoming the challenges of high-precision tasks in extreme and unstructured environments. His work centers on developing robust control and perception strategies for complex assembly operations, particularly in space and industrial settings. Gan’s major contributions include pioneering the application of the "attractive region in environment" (ARIE) method for compliant peg-in-hole assembly of nonconvex and nonstandard components, a critical advancement for automated manufacturing. His most cited paper, "High performance assembly of complex structural parts in special environments – research on space manipulator assisted module docking method" (2023, 15 citations), addresses the degradation of robot and sensor accuracy in space, proposing a novel docking method for module assembly. Additionally, his recent work on continual learning for generalized grasping in musculoskeletal robots (2025) tackles the challenge of dynamic task adaptation, showcasing his forward-looking approach to robotic dexterity. With a growing citation record and a focus on real-world applications from orbital assembly to adaptive manipulation, Gan’s research is shaping the future of autonomous robotic systems in demanding environments.
Research Focus
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Top Papers
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