Papers
9
Total Citations
68
H-Index
6
About
Yijun Yuan is a robotics researcher whose work centers on topological mapping, autonomous navigation, and 3D reconstruction for mobile and rescue robots. His most significant contribution is the development of the **Area Graph**, a novel topological map representation built using Voronoi diagrams that drastically reduces storage and computational demands for path planning and map matching—his foundational paper on this topic has accumulated 19 citations. Yuan also pioneered an **incremental topology graph construction framework** using distance maps, enabling real-time mapping without pre-built environments (10 citations). In rescue robotics, he advanced **configuration-space flipper planning** for tracked robots navigating unstructured 3D terrain, with multiple papers totaling over 14 citations that address autonomous morphology adaptation. More recently, Yuan has ventured into **neural rendering**, proposing an online learning method for neural surface light fields integrated with incremental 3D reconstruction, achieving novel view synthesis in real time—a breakthrough for operator-based human-robot interaction. His work bridges efficient spatial representation with practical autonomy, earning recognition for both theoretical rigor and deployable solutions in challenging environments.
Research Focus
Key Achievements
Top Papers
- 1Area Graph: Generation of Topological Maps using the Voronoi Diagram19 citations · 2019
- 2Incrementally Building Topology Graphs via Distance Maps10 citations · 2019
- 3Fast Gaussian Process Occupancy Maps9 citations · 2018
- 4Configuration-Space Flipper Planning for Rescue Robots8 citations · 2019
- 5Matching maps based on the Area Graph7 citations · 2022
- 6Configuration-Space Flipper Planning on 3D Terrain6 citations · 2020
- 7
- 8Area Graph: Generation of Topological Maps using the Voronoi Diagram3 citations · 2019
- 9Topological Area Graph Generation and its Application to Path Planning2 citations · 2018