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About

Zhidong Su is a robotics and artificial intelligence researcher whose work sits at the intersection of autonomous navigation, social robotics, and intelligent eldercare systems. His research spans two primary domains: simultaneous localization and mapping (SLAM) for mobile robots, and the development of companion robot platforms designed to support aging populations. Su's most influential contribution is his improved ORB-SLAM2 algorithm for rapid mobile robot relocalization, which has garnered 125 citations and introduced a novel binary vocabulary training method that significantly accelerates real-time positioning. His comparative analysis of visual SLAM methodologies further established a foundation for understanding feature-based versus direct approaches in social robot navigation. Equally notable is Su's sustained focus on eldercare technology. Through a series of progressively sophisticated systems, he has developed conversation-based medication management, multimodal activity monitoring using wearable devices and companion robots, and emotion regulation systems that interpret ECG signals to address negative affect in older adults. These contributions, collectively accumulating hundreds of citations, reflect a coherent research vision: making robots practical, empathetic caregivers for aging populations. Su's body of work demonstrates rare breadth — combining low-level robotic perception with high-level human-robot interaction — making him a distinctive voice in the field of intelligent assistive robotics.