Papers
8
Total Citations
300
H-Index
6
About
Ben Burgess-Limerick is a robotics researcher whose work sits at the intersection of robotic learning, mobile manipulation, and perception. He is best known for his contributions to the Open X-Embodiment project, a landmark collaboration that produced one of the largest and most diverse robotic learning datasets to date. His co-authored papers on this effort have already garnered over 200 citations, reflecting the project’s profound impact on the field of generalist robot learning. Beyond large-scale data, Burgess-Limerick has pioneered methods for reactive mobile manipulation “on-the-move,” developing control architectures that allow robots to grasp and manipulate objects while their base is still in motion—dramatically reducing cycle times in dynamic environments. His work on visibility maximization controllers addresses the persistent challenge of self-occlusion in eye-to-hand camera setups, and he introduced DGBench, an open-source benchmark for reproducible dynamic grasping evaluation. With a focus on real-world deployment, including failure recovery and field robotics, Burgess-Limerick’s research is shaping how robots operate reliably and efficiently in unstructured, human-centric spaces.
Research Focus
Key Achievements
Top Papers
- 1
- 2Open X-Embodiment: Robotic Learning Datasets and RT-X Models101 citations · 2023
- 3Visibility Maximization Controller for Robotic Manipulation25 citations · 2022
- 4An Architecture for Reactive Mobile Manipulation On-The-Move22 citations · 2023
- 5
- 6DGBench: An Open-Source, Reproducible Benchmark for Dynamic Grasping11 citations · 2022
- 7
- 8Enabling Failure Recovery for On-The-Move Mobile Manipulation2 citations · 2023