Changlin He

Papers

Total Citations

H-Index

About

Changlin He is a pioneering researcher in mobile robotics, with a primary focus on autonomous navigation, obstacle avoidance, and path tracking control. His most influential work, "Study of the New Method for Improving Artificial Potential Field in Mobile Robot Obstacle Avoidance" (2007, 29 citations), addresses critical limitations of the traditional artificial potential field (APF) method—specifically the local trap and vibration problems. He proposed a novel force function that significantly enhances robot mobility in cluttered environments, validated through simulation. This contribution remains a foundational reference for researchers seeking to improve reactive navigation algorithms. He also advanced the field of automated guided vehicles (AGVs) through his experimental study on multi-step predictive control for path tracking, applied to the differential-drive XAUT.AGV100. This work demonstrated practical solutions for nonholonomic constraint challenges in unmanned production workshops. While his citation counts reflect focused, early-career impact, He’s innovations in APF optimization and predictive control continue to inform modern developments in warehouse automation and intelligent transportation systems.