Papers
16
Total Citations
607
H-Index
8
About
Yulun Tian is a robotics researcher whose work sits at the intersection of multi-robot systems, simultaneous localization and mapping (SLAM), and distributed algorithms. He is best known as a lead architect of **Kimera-Multi**, a landmark system enabling teams of robots to collaboratively build dense, metric-semantic 3D maps of their environments in real time — work that has garnered over 300 citations across its iterations and represents the first fully distributed multi-robot metric-semantic SLAM system of its kind. His research consistently tackles the hardest practical challenges in collaborative robotics: perceptual aliasing, limited communication bandwidth, and the need for robust operation in GPS-denied, unstructured environments such as forest canopies, where his UAV-based search-and-rescue system demonstrated compelling real-world impact. Beyond system-building, Tian has made foundational algorithmic contributions, including asynchronous distributed pose graph optimization and resource-aware loop closure detection with provable performance guarantees — work that directly addresses scalability in multi-robot deployments. His more recent research on object-based global localization and spectral sparsification signals a continued push toward robust, communication-efficient autonomy. Across his career, his publications have accumulated over 550 citations, establishing him as a rising authority in collaborative robot perception.
Research Focus
Key Achievements
Top Papers
- 1
- 2Search and rescue under the forest canopy using multiple UAVs122 citations · 2020
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- 4Asynchronous and Parallel Distributed Pose Graph Optimization45 citations · 2020
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- 7Near-Optimal Budgeted Data Exchange for Distributed Loop Closure Detection27 citations · 2018
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