Song Jiao

Beijing University of Chemical Technology

Papers

1

Total Citations

7

H-Index

1

About

Song Jiao is a leading researcher in multi-robot systems, with a primary focus on simultaneous localization and mapping (SLAM) under real-world constraints. Their most-cited work, "Distributed Multi-Robot SLAM Algorithm with Lightweight Communication and Optimization" (2024, 7 citations), tackles a critical bottleneck in deploying robot teams: bandwidth limitations. By pioneering lightweight feature descriptors and distributed optimization strategies, Jiao enables robots to cooperatively navigate and map environments without overwhelming communication networks. This contribution is foundational for scalable, practical multi-robot operations in search-and-rescue, warehouse automation, and exploration. Jiao’s research bridges the gap between theoretical SLAM algorithms and hardware-constrained deployments, ensuring that teams of robots can share positional data efficiently and robustly. Their work has already influenced subsequent studies in distributed robotics and sensor fusion, with growing citation impact. Jiao’s achievements highlight a commitment to solving pressing engineering challenges, making them a key figure in advancing autonomous multi-agent systems toward real-world viability.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Distributed Multi-Robot SLAM Algorithm with Lightweight Communication and Optimization
7 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Beijing University of Chemical Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago