Max Robotics — Global Service Robot Directory + US Certification

About

Yiying Li is a pioneering researcher at the intersection of cloud robotics, multi-robot systems, and federated learning, whose work has fundamentally reshaped how robots perceive, learn, and collaborate in dynamic environments. Li’s major contributions center on developing architectures that enable robots to transcend their local computational constraints by leveraging cloud resources and Internet knowledge. Their seminal 2018 paper on differential federated learning for multi-robot real-time data processing (30 citations) introduced a groundbreaking framework that balances privacy preservation with efficient collaborative learning across robot swarms. Li’s 2016 work on QoS-aware cloud robotic applications (19 citations) established a hybrid architecture that remains influential in the field, while their RoboCloud system (2018) pioneered the augmentation of robotic vision using Internet-scale knowledge for open environment modeling. Notably, Li has advanced deep learning-based cooperative trail following for multi-robot systems and developed novel approaches to fast adaptation in multi-agent reinforcement learning, addressing the critical challenge of integrating newcomers into established robot teams. Their work on learning from Internet sources has opened new pathways for robots to handle environmental uncertainty. With a research portfolio spanning over 70 citations, Yiying Li stands as a key architect of the next generation of ubiquitous, cloud-connected robotic intelligence.