Ling Lingzhou

China University of Mining and Technology

Papers

Total Citations

H-Index

About

Ling Lingzhou is a researcher focused on advancing robotic perception and autonomous navigation in hazardous environments, particularly underground and post-disaster settings. Their most-cited work, “Research on stereo vision matching algorithm for rescue robot” (2017, 5 citations), addresses a critical challenge in mine rescue operations: after coal mine gas explosions, narrow tunnels and limited access demand real-time environmental feedback and victim localization. Lingzhou’s major contribution lies in developing stereo vision matching algorithms that enable rescue robots to perceive depth and structure in low-visibility, confined spaces, directly improving the speed and safety of emergency response. This work bridges computer vision and field robotics, offering practical solutions for life-saving automation. While their citation count is modest, the research holds significant applied value for mining safety and disaster robotics, reflecting a commitment to technology that serves urgent human needs. Lingzhou’s contributions are notable for their focus on real-world deployment constraints, making them a valuable voice in the niche but vital field of rescue robotics.