Chih-Chun Cheng

National Taiwan University, National Chung Cheng University

Papers

Total Citations

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About

Chih-Chun Cheng is a roboticist whose research lies at the intersection of machine learning, control theory, and manipulation. His most influential work, *"Learning the Inverse Dynamics of Robotic Manipulators in Structured Reproducing Kernel Hilbert Space"* (2015, 27 citations), tackles a fundamental challenge: modeling a robot’s inverse dynamics without relying on prior kinematic knowledge. This approach offers a more flexible and efficient alternative to rigid-body models, enabling robots to compensate for complex dynamics and friction in real-world tasks. Cheng’s work in grasp synthesis and control, detailed in his 2015 paper, further demonstrates his focus on practical dexterity—using tactile feedback to manage uncertainty during hand-arm grasping. More recently, his 2023 paper on smooth interpolation with corner tolerance constraints addresses the critical need for continuous, precise trajectory generation in robotic motion planning. By combining theoretical rigor with application-driven solutions, Cheng has made meaningful contributions to making robots more adaptive and reliable in unstructured environments. His research is particularly valuable for students and engineers working at the frontier of learning-based control and autonomous manipulation.