Yu Huo

University of Chinese Academy of Sciences

Papers

Total Citations

H-Index

About

Yu Huo is a researcher in robotics and computer vision, with a focus on spatial perception and autonomous systems. Their most notable contribution is the development of a spatial self-calibration algorithm for robot vision, published in 2018. This work addresses a critical challenge in robotics—enabling robots to autonomously calibrate their visual sensors without external references, thereby enhancing adaptability in unstructured environments. While the citation count for this paper remains modest at two, the algorithm represents a foundational step toward more robust and self-reliant robotic systems, particularly in applications like mobile manipulation and autonomous navigation. Huo’s research sits at the intersection of sensor fusion, geometric modeling, and machine learning, aiming to reduce human intervention in calibration processes. Though early in their career, Huo’s work contributes to the broader goal of creating vision systems that can operate reliably in real-world conditions. As the field of robot vision continues to evolve, Huo’s self-calibration approach may prove valuable for future autonomous platforms requiring minimal setup and maintenance.