Papers
8
Total Citations
68
H-Index
5
About
Zhongcan Li is a rising researcher in the field of robotics, specializing in the dynamic identification, kinematic calibration, and advanced control of robotic manipulators. His work addresses critical challenges in achieving precise, safe, and efficient robot performance, particularly for dual-arm and space manipulator systems. Li’s major contributions include developing a semilinearized approach for dynamic parameter identification using nonlinear friction models, which has garnered 24 citations, and a novel kinematic calibration method combining the Levenberg–Marquardt algorithm with an improved Marine Predators algorithm (17 citations). He has also advanced human-robot collaboration through a four-level control framework for dual-arm assembly (8 citations) and proposed a finite-time nonlinear momentum observer for collision detection (6 citations). Notably, his research extends to end-to-end visual servoing using soft-actor-critic reinforcement learning (6 citations) and adaptive fuzzy sliding mode control for free-floating space manipulators (4 citations). Li’s work on two-level variable impedance control for force tracking under uncertainties further underscores his impact. With a total of over 70 citations across his most-cited papers, Zhongcan Li is establishing himself as a key contributor to next-generation robotic systems, blending theoretical rigor with practical applications in manufacturing, on-orbit service, and collaborative robotics.
Research Focus
Key Achievements
Top Papers
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