Max Robotics — Global Service Robot Directory + US Certification

About

Ruofei Bai is an emerging researcher whose work sits at the intersection of multi-robot systems, autonomous exploration, and formal methods for task planning. His research addresses some of the most challenging problems in robotics: enabling teams of robots to coordinate intelligently, navigate unknown environments reliably, and satisfy complex mission specifications simultaneously. Bai's contributions span two complementary directions. In task planning, he has developed frameworks that allow multi-robot systems to fulfill both individual and collaborative temporal logic specifications, producing feasible, optimized strategies through hierarchical synthesis approaches — work that has accumulated over 20 citations across two closely related publications. In autonomous exploration, he has advanced SLAM-aware planning methods that leverage prior topological and metric information to dramatically improve mapping efficiency, while his submodular optimization approach to multi-robot active graph exploration addresses the difficult trade-off between coverage and localization uncertainty. His more recent work on line-of-sight connectivity maintenance during navigation in unknown environments reflects a growing focus on communication-aware multi-robot coordination. With publications in leading venues and a rapidly growing citation record, Bai represents a promising voice in robotics research, particularly for students interested in bridging formal verification techniques with practical autonomous systems.