Jinglin Zhang

University of Chinese Academy of Sciences, Tianma Microelectronics (China), Nanjing University of Information Science and Technology

Papers

Total Citations

H-Index

About

Jinglin Zhang is a researcher focused on robotics, computer vision, and autonomous navigation, with particular expertise in SLAM (Simultaneous Localization and Mapping) and stereo vision algorithms. Zhang’s most cited work, “An approach to restaurant service robot SLAM” (2016, 14 citations), introduced a practical system using depth cameras for real-time localization and mapping in dynamic indoor environments, addressing a critical need for service robots in human-centric spaces. This contribution laid groundwork for integrating SLAM into everyday robotic applications. In “Research on the Body Positioning Method of Bolting Robots Based on Monocular Vision” (2023, 6 citations), Zhang tackled the challenge of precise positioning in underground mining environments, proposing a monocular vision-based method for unmanned excavation faces—a notable achievement in industrial automation. Additionally, “Improving stereo matching algorithm with adaptive cross-scale cost aggregation” (2018, 5 citations) advanced dense stereo correspondence by incorporating bio-inspired multi-scale processing, enhancing accuracy for applications in robot navigation and autonomous driving. With a growing citation record, Zhang’s work bridges theoretical vision algorithms and real-world robotic systems, demonstrating significant impact in service robotics, mining automation, and 3D perception.