Yinan Yu

Horizon Robotics (China), Thomas Jefferson University

Papers

Total Citations

183

H-Index

About

Yinan Yu is a leading researcher in robotics and computer vision, with a primary focus on sensor fusion and depth estimation for autonomous systems. Her most impactful contribution is the development of methods to reconstruct dense 3D geometry from sparse sensor data, as demonstrated in her highly cited work "Parse Geometry from a Line: Monocular Depth Estimation with Partial Laser Observation" (2017, 126 citations). This research addresses a critical challenge in robotics: enabling platforms equipped only with a monocular camera and a 2D laser range finder—common on many standard robots—to achieve reliable depth perception without expensive 3D sensors. By leveraging partial laser observations, Yu’s approach significantly enhances a robot’s ability to navigate and interact with complex environments. Additionally, she has made notable contributions to medical robotics, particularly in her 2011 paper on a robotic approach to 4D real-time tumor tracking for radiotherapy (51 citations). This work tackles the problem of respiratory and cardiac motion during treatment, proposing a robotic system to track tumor movement in real time, thereby reducing the need for large safety margins and improving precision. Yu’s research bridges practical hardware limitations with advanced algorithmic solutions, making her work highly influential in both industrial robotics and clinical applications.