Erke Shang

National University of Defense Technology, Academy of Military Medical Sciences

Papers

Total Citations

H-Index

About

Erke Shang’s research advances the autonomy of field and security robots, with a focus on perception, calibration, and multi-robot planning. His most cited work, “A fast calibration approach for onboard LiDAR-camera systems” (2020, 6 citations), addresses a critical bottleneck in outdoor surveillance and security robotics by enabling rapid, accurate sensor fusion—essential for reliable autonomous navigation in real-world environments. Building on this, Shang developed a feature matching and fusion-based algorithm for positive obstacle detection (2017, 4 citations), specifically designed to protect field autonomous land vehicles from collision damage during traversal. His contributions extend to multi-robot coordination through a novel three-layer-architecture planning method (2022, 2 citations) for heterogeneous autonomous land vehicles, integrating global road networks, path planning, and task allocation. Though early in his career, Shang’s work is notable for its practical, system-level approach to field robotics—tackling the real-world challenges of sensor calibration, obstacle detection, and heterogeneous fleet management. His research directly supports the deployment of autonomous vehicles in industrial, military, and civilian applications, laying groundwork for safer, more capable field robotics.