Max Robotics — Global Service Robot Directory + US Certification

About

Qi She is a pioneering researcher at the intersection of robotic vision, lifelong learning, and autonomous systems, whose work addresses one of the most pressing challenges in modern robotics: enabling machines to learn and adapt continuously in real-world environments. She is best known for developing the **OpenLORIS** suite of datasets — including OpenLORIS-Scene and OpenLORIS-Object — which have become landmark benchmarks for evaluating lifelong SLAM and object recognition in service robot contexts. Her 2020 paper on OpenLORIS-Scene datasets has garnered over 163 citations, reflecting its significant influence on the robotics and SLAM communities. She's research tackles the critical gap between standard computer vision benchmarks and the dynamic, unpredictable conditions robots encounter in everyday settings. By introducing datasets specifically designed for incremental and lifelong learning scenarios, she has helped reframe how the field evaluates algorithmic robustness over time. Her organization of the IROS 2019 Lifelong Robotic Vision Challenge, which attracted over 150 competing teams, further demonstrates her role as a community builder driving progress in assistive and service robotics. Her body of work provides essential infrastructure for researchers striving to build truly autonomous, adaptable robots.