Xiangyang Zhi

ShanghaiTech University, Nitto (United States)

Papers

Total Citations

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About

Xiangyang Zhi is a leading researcher in robotics and autonomous systems, with a primary focus on sensor calibration, perception, and autonomous exploration. His most impactful contribution is the development of novel pipelines for hand-eye calibration, as detailed in his highly cited 2017 paper (38 citations), which eliminates the need for traditional calibration targets. This work has significantly streamlined the process of determining the transformation between a robot’s gripper and its mounted camera, a fundamental challenge in robotic manipulation. Zhi further advanced the field with "Multical" (2022, 11 citations), a general spatiotemporal calibration method for multiple heterogeneous sensors—including IMUs, cameras, and LiDARs—that is critical for robust perception in autonomous driving and robotics. Beyond calibration, he has addressed the challenge of autonomous exploration and mapping with semantic vision (2019, 11 citations), enabling mobile robots to intelligently navigate and map unknown environments. Through these contributions, Zhi has provided foundational tools that enhance the accuracy and autonomy of robotic systems, making him a notable figure in modern robotics research.