Zhe Zhao

Beijing Research Institute of Mechanical and Electrical Technology

Papers

Total Citations

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About

Zhe Zhao is a researcher focused on advancing perception and human-robot interaction in indoor environments, particularly through multimodal sensor fusion. Their major contribution lies in developing robust methods for pedestrian detection and tracking by integrating 2D Lidar with RGB-D cameras. This work addresses a critical challenge in human-robot coexisting spaces: accurately distinguishing people from objects and estimating pedestrian pose and speed in real time. By combining depth and visual data, Zhao’s approach enhances the reliability of mobile robots navigating dynamic indoor settings, directly supporting safer and more intuitive human-robot collaboration. While their most cited paper, "Pedestrian detection and tracking based on 2D Lidar and RGB-D camera" (2022), has garnered 2 citations, it represents foundational work in a niche but growing field. Zhao’s research is particularly notable for its practical application in robotics, where precise perception is key to autonomous operation. Their achievements underscore a commitment to bridging sensor technology and real-world deployment, making their work valuable for students and researchers exploring sensor fusion, autonomous navigation, and human-aware robotics.