Haotian Shen

Shanghai Jiao Tong University, Guangxi University

Papers

Total Citations

H-Index

About

Haotian Shen is a leading researcher in intelligent robotic systems, with a primary focus on welding automation, computer vision, and real-time path planning. His work bridges the gap between traditional manufacturing and autonomous robotics, addressing critical challenges in industrial applications. Shen’s most influential contribution is his pioneering research on weld pool control for gas tungsten arc welding (GTAW) robots, where he developed vision-based systems to overcome gap variations during the welding process—a key limitation of conventional "teach and playback" robots. This work, published in 2007, has garnered 43 citations and laid the foundation for adaptive robotic welding. He further advanced seam tracking with real-time vision techniques (18 citations), enabling robots to dynamically adjust to workpiece misalignments. More recently, Shen introduced DBVSB-P-RRT*, a path planning algorithm achieving ultra-high speed and environmental adaptability (24 citations in 2024), marking a significant leap in mobile robot navigation. His research is characterized by a practical, problem-driven approach that directly impacts manufacturing efficiency and robotic autonomy. With a growing citation record and continuous innovation, Shen is shaping the future of intelligent, vision-guided robotic systems for complex industrial environments.