Yihao Liu

Chinese Academy of Sciences, Johns Hopkins University

Papers

Total Citations

H-Index

About

Yihao Liu is a robotics researcher whose work spans multi-robot systems, surgical robotics, and human-robot interaction. His key contributions include developing UWB-VIO fusion techniques that achieve accurate and robust relative localization for ground robot teams, addressing a fundamental challenge in infrastructure-free multi-robot coordination. He also introduced GBEC (Geometry-Based Hand-Eye Calibration), a novel approach that improves upon traditional regression-based methods for solving the robot-to-sensor transformation problem. In the medical domain, Liu has pioneered mixed reality systems for robotic-assisted medical instrument planning and execution, enabling on-the-fly anatomical targeting. His most recent work, dARt Vinci, presents an innovative egocentric data collection framework for surgical robot learning, tackling the critical issue of data scarcity in safety-critical applications. With his most cited paper accumulating 29 citations, Liu's research demonstrates growing impact in both theoretical calibration problems and practical surgical robotics applications. His work at the intersection of perception, calibration, and medical robotics positions him as an emerging contributor to autonomous robotic systems.