Yanliang Chen
Papers
1
Total Citations
5
H-Index
1
About
Yanliang Chen is a leading researcher in multi-robot cooperative simultaneous localization and mapping (SLAM), a critical area for autonomous systems and robotics. His most-cited work, "Multi-Robot Cooperative Simultaneous Localization and Mapping Algorithm Based on Sub-Graph Partitioning" (2025, 5 citations), tackles the fundamental challenges of scalability and efficiency in multi-robot SLAM. Chen’s key contribution is a novel sub-graph partitioning algorithm that dramatically reduces redundant computations and streamlines candidate loop closure selection during front-end loop detection. By partitioning the global map into manageable sub-graphs, his approach also lowers the computational complexity and iteration times associated with global pose optimization, enabling faster and more reliable mapping in large-scale environments. This work is particularly impactful for applications in search-and-rescue, warehouse automation, and exploration. With a growing citation record, Chen is recognized for advancing practical, real-time multi-robot coordination, making his research essential reading for students and engineers working on collaborative autonomy and distributed robotic systems.
Research Focus
Key Achievements
Top Papers
- 1