Teng Huang

Beijing Institute of Technology, Hohai University, Karlsruhe Institute of Technology

Papers

Total Citations

173

H-Index

About

Teng Huang is a robotics researcher whose work centers on control theory, perception, and autonomous manipulation. His most influential contribution is a robust model predictive tracking control algorithm for robot manipulators, published in 2020. This work, which has garnered 132 citations, addresses the challenge of time-varying trajectory tracking under disturbances while respecting joint state constraints and input torque limits—a critical advancement for real-world robotic applications. Huang also made notable contributions to sensor calibration, developing a novel RGB-D camera calibration model based on 3D control fields, which improves accuracy for depth and pose estimation in robotics and computer vision. Additionally, his research on predicting pushing action effects through learned internal models demonstrates a sophisticated approach to enabling robots to reason about action consequences before execution. By combining robust control with perceptual precision and predictive modeling, Huang’s work bridges fundamental theory and practical deployment, offering valuable tools for researchers and engineers working on autonomous systems.