Shuai Yu

Papers

1

Total Citations

2

H-Index

1

About

Shuai Yu is a leading researcher at the intersection of edge computing and robotics, with a primary focus on accelerating multi-robot systems through intelligent network architectures. His most cited work, "Edge Robotics: Edge-Computing-Accelerated Multi-Robot Simultaneous Localization and Mapping" (2021), addresses a critical bottleneck in collaborative robotics: the performance contradiction between computation-heavy SLAM algorithms and the limited onboard resources of individual robots. By offloading key processing tasks to edge servers, Yu’s research enables faster, more accurate multi-robot localization and mapping—a breakthrough with direct implications for autonomous warehouses, search-and-rescue operations, and industrial automation. While his citation count is still growing, the foundational nature of this work has positioned him as an emerging voice in edge-accelerated robotics. Yu’s contributions are particularly notable for bridging the gap between distributed computing theory and practical robotic deployment, offering a scalable solution to one of the field’s most persistent challenges. For students and researchers exploring the convergence of edge intelligence and multi-agent systems, Yu’s work provides a clear roadmap for future innovation.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Edge Robotics: Edge-Computing-Accelerated Multi-Robot Simultaneous Localization and Mapping
2 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 5

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago