Shulin Feng

Papers

Total Citations

H-Index

About

Shulin Feng’s research lies at the intersection of mobile robotics, multi-agent coordination, and intelligent control systems. His work focuses on enabling autonomous robots to track moving targets, form stable formations, and execute complex cooperative tasks like interception and hunting. In his most cited paper, Feng improved the line-of-sight guidance law for robot tracking by integrating an optimal information fusion Kalman filter, which significantly enhanced trajectory precision in the presence of sensor noise—a critical advancement for real-world autonomous navigation. His 2011 paper on formation control introduced a consensus protocol for wheeled mobile robots, validated through an AmigoBot platform communicating over a wireless local area network, laying groundwork for decentralized multi-robot coordination. Feng also developed control algorithms for interception and hunting behaviors, using input-output feedback linearization to enable two robots to collaboratively pursue a single target. Though his citation counts (11, 8, and 4) reflect focused, early-career impact, his contributions to practical, experimentally validated control strategies for mobile robot teams are notable. Feng’s work offers a solid foundation for researchers exploring cooperative robotics, sensor fusion, and real-time trajectory control.