Max Robotics — Global Service Robot Directory + US Certification

About

Shan An is a versatile robotics and computer vision researcher whose work spans simultaneous localization and mapping (SLAM), UAV tracking, human-computer interaction, and embedded systems intelligence. His most cited contribution, "Multi-Regularized Correlation Filter for UAV Tracking and Self-Localization" (2021, 84 citations), advances discriminative correlation filter frameworks to significantly improve aerial vehicle tracking robustness. Complementing this, his pioneering work on loop closure detection — including both the proximity graph-based approach (2019, 43 citations) and its deep feature-enhanced successor (2022, 53 citations) — has meaningfully accelerated visual SLAM systems, addressing critical speed and recall challenges that previously limited real-world deployment. An has also demonstrated a consistent drive toward practical, resource-constrained applications, developing efficient architectures for monocular hand pose estimation, human depth estimation, and fall detection optimized for embedded devices. His early work on SURF-based face detection for human-robot interaction (2009, 24 citations) reflects a long-standing commitment to bridging perception and robotics. More recently, contributions to semi-supervised segmentation and surgical action recognition highlight his expanding influence in medical and autonomous systems. With over 300 cumulative citations across diverse domains, An represents a productive and broad-minded contributor to intelligent robotic perception.