Max Robotics — Global Service Robot Directory + US Certification

About

Baoxing Qin is a leading researcher in robotics, specializing in lifelong SLAM (Simultaneous Localization and Mapping), service robotics, and deep learning for autonomous systems. His most significant contribution is the development of the OpenLORIS-Scene datasets, a benchmark that has become foundational for evaluating SLAM algorithms in dynamic, real-world environments—a critical step toward truly autonomous service robots. This work, his most cited with over 163 citations, addresses the fundamental challenge of robots operating reliably in changing spaces like malls and homes over extended periods. Qin also proposed a general framework for lifelong localization and mapping, enabling robots to maintain accurate maps despite environmental changes, a key advancement for long-term deployment. His recent work extends into deep reinforcement learning for vehicle routing problems and AI-driven cleaning systems, showcasing his versatility. With a citation count exceeding 240, Qin’s research directly tackles the gap between laboratory robotics and real-world application, making him a pivotal figure in the push for robots that can adapt, learn, and serve in our daily lives.