Yuhan Dong
Papers
2
Total Citations
13
H-Index
2
About
Yuhan Dong is a robotics researcher whose work spans multi-robot perception, warehouse automation, and 3D scene understanding. His most notable contribution is the development of MR-COGraphs, a communication-efficient multi-robot open-vocabulary mapping system that leverages 3D scene graphs and foundation models. This work, published in 2025 and already garnering 7 citations, addresses the critical challenge of enabling robot teams to collaboratively perceive unknown environments while understanding not just geometry but semantic content through open-vocabulary queries. The system's efficiency in communication makes it particularly valuable for real-world deployment where bandwidth is limited. Earlier, Dong made significant contributions to warehouse logistics through his work on optimizing pod point matching decisions in Robotic Mobile Fulfillment Systems (RMFS). His 2020 paper, with 6 citations, tackled the fundamental problem of selecting optimal storage positions for pods after picking tasks, offering two distinct optimization perspectives that improve system throughput. Dong's research sits at the intersection of practical robotics deployment and cutting-edge AI, demonstrating how foundation models can transform multi-robot coordination from simple geometric mapping to rich, semantically-aware collaboration.
Research Focus
Key Achievements
Top Papers
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- 2