Max Robotics — Global Service Robot Directory + US Certification

About

Qiwei Long is a robotics researcher whose work centers on Simultaneous Localization and Mapping (SLAM), autonomous navigation, and the real-world deployment of service robots. His research addresses one of the most pressing challenges in modern robotics: enabling robots to operate reliably in dynamic, ever-changing environments over extended periods of time. Long is perhaps best known for his contributions to the OpenLORIS-Scene datasets, a landmark benchmarking resource designed to evaluate lifelong SLAM systems under realistic, everyday conditions — work that has accumulated over 180 citations and has become an important reference point for researchers assessing the true readiness of service robots. Equally influential is his development of DXSLAM, a robust and efficient visual SLAM system that integrates deep learning-based feature extraction to overcome longstanding limitations in traditional hand-engineered pipelines, garnering over 155 citations. Together, these contributions reflect Long's commitment to bridging the gap between theoretical SLAM frameworks and practical robotic autonomy. His work has meaningfully shaped how the robotics community evaluates and builds next-generation navigation systems, making him a notable voice in the field of intelligent and lifelong robot learning.