Cheng Han

National Taipei University of Technology

Papers

Total Citations

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About

Cheng Han is a researcher specializing in robotics and intelligent control systems, with a particular focus on redundant manipulators and motion planning. His work addresses critical challenges in robotic kinematics, especially the persistent problem of singularity avoidance—a key obstacle in ensuring smooth, uninterrupted robot operation. In his notable study, "Singularity Avoidance for a Redundant Robot Using Fuzzy Motion Planning" (2013), Han proposed an innovative approach that integrates fuzzy logic with motion planning to overcome the limitations of the Moore-Penrose pseudo-inverse kinematic method. While the pseudo-inverse is widely used for solving inverse kinematics, it fails in singular configurations; Han’s fuzzy-based strategy offers a more robust solution, enabling redundant robots to track specific trajectories without encountering singularities. Though his work has garnered 4 citations, its conceptual contribution to adaptive robotic control is significant for researchers developing safer, more reliable automation systems. Han’s research bridges theoretical kinematics and practical robotic design, making his insights valuable for students and engineers working on advanced manipulator control and human-robot interaction.