Yimei Kang

Beihang University, Chinese Academy of Sciences

Papers

Total Citations

H-Index

About

Yimei Kang is a researcher specializing in robotic localization, sensor fusion, and computer vision, with a focus on improving the accuracy and adaptability of autonomous systems. Her most impactful work addresses a fundamental challenge in time-of-arrival (TOA)-based localization: the strict requirement for time synchronization between targets and sensors. In her 2018 paper, which has garnered 51 citations, Kang proposed a high-accuracy TOA method that eliminates the need for synchronization in three-dimensional space, significantly enhancing localization precision for robotic systems. This contribution is critical for applications in autonomous navigation and distributed sensor networks. Kang also advanced visual tracking with her scale-adaptive Mean-Shift (SAMSHIFT) algorithm, published in 2013, which overcomes the limitations of traditional Mean-Shift tracking when handling scale changes and occlusions. While her citation count reflects a growing influence, her work demonstrates a clear trajectory toward solving practical, real-world constraints in robotics. Kang’s research is particularly valuable for engineers and students working on localization, tracking, and autonomous systems, offering innovative solutions that bridge theoretical gaps and operational demands.