Papers
5
Total Citations
133
H-Index
4
About
Yingrui Jie is a leading researcher in autonomous robotics, specializing in large-scale exploration, multi-robot systems, and heterogeneous perception. His work addresses the fundamental challenge of enabling robots—both ground and aerial—to navigate and map unknown environments efficiently and autonomously. Jie’s most impactful contribution is the FAEL framework (77 citations), which introduces a fast autonomous exploration algorithm designed to overcome computational bottlenecks in large-scale environments, allowing mobile robots to respond to environmental changes in real time. He further advanced the field with GRACO (33 citations), a pioneering multimodal dataset for ground and aerial cooperative localization and mapping, filling a critical gap in large outdoor scenes. Jie’s research also explores decentralized connectivity maintenance for multi-robot teams using reinforcement learning, and heterogeneous deep metric learning for place recognition across different platforms. His work on floor feature-based indoor positioning, though earlier, demonstrates his versatility. With a growing citation impact and a focus on practical, scalable solutions, Jie is shaping the future of autonomous navigation in complex, real-world environments.
Research Focus
Key Achievements
Top Papers
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- 5Indoor Robot Visual Positioning System Based on Floor Features2 citations · 2018