Papers
13
Total Citations
1,361
H-Index
9
About
Glenn Wagner is a leading researcher in multi-robot systems, with a primary focus on multi-agent path planning (MAPF) and autonomous exploration in complex, unstructured environments. His most significant contribution is the development of **subdimensional expansion**, a foundational framework that dramatically reduces the computational complexity of multi-robot path planning by initially planning for each robot individually and then coordinating motion among coupled robots only when necessary. This work, detailed in his highly cited papers on **M*** and **PRIMAL**, has enabled scalable solutions for large-scale robot deployments, from warehouse automation to aerial swarms, with his top-cited paper alone garnering nearly 400 citations. Wagner also played a pivotal role in **Team CSIRO Data61's** success at the **DARPA Subterranean Challenge**, where he led the development of heterogeneous teams of ground and aerial robots capable of autonomously exploring dangerous, GPS-denied underground environments. His work on frontier-based exploration using direct point cloud visibility has been instrumental in advancing the state of the art in autonomous subterranean exploration, demonstrating the real-world impact of his theoretical contributions.
Research Focus
Key Achievements
Top Papers
- 1PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learning399 citations · 2019
- 2Subdimensional expansion for multirobot path planning372 citations · 2014
- 3M*: A complete multirobot path planning algorithm with performance bounds240 citations · 2011
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- 5ODrM* optimal multirobot path planning in low dimensional search spaces75 citations · 2013
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- 9Rapid Randomized Restarts for Multi-Agent Path Finding Solvers12 citations · 2021
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