Zuhao Zou

Hong Kong University of Science and Technology, Shenzhen Institutes of Advanced Technology

Papers

Total Citations

H-Index

About

Zuhao Zou is a robotics researcher whose work lies at the intersection of perception, calibration, and autonomous navigation. His most impactful contribution is in the domain of hand-eye calibration (HEC), a critical technique for precision industrial visual servoing and robotic grasping. In his highly cited 2020 paper, "Globally Optimal Symbolic Hand-Eye Calibration" (18 citations), Zou addressed long-standing limitations in existing closed-form and iterative HEC solutions by introducing a globally optimal symbolic approach, significantly improving accuracy and reliability for real-world robotic systems. Beyond calibration, Zou has contributed to autonomous driving perception, notably through his 2019 work on "Road Curb Detection Using A Novel Tensor Voting Algorithm" (5 citations). This method processes dense point cloud data to robustly detect road curbs, enhancing the safety and robustness of outdoor robot navigation. By tackling both foundational calibration problems and applied perception challenges, Zou demonstrates a rare ability to bridge theoretical optimization with practical deployment. His work continues to influence advances in industrial robotics and autonomous vehicle systems.