Papers

5

Total Citations

236

H-Index

3

About

Charlotte Le is a leading researcher at the forefront of robotic manipulation and cloud robotics, whose work is shaping how robots learn and operate in the real world. Her primary contributions lie in creating large-scale, diverse datasets and scalable systems that bridge the gap between laboratory robots and practical, in-the-wild applications. Le is a key contributor to the landmark **Open X-Embodiment** collaboration (119 citations), which demonstrated that training high-capacity models on heterogeneous robotic data can produce generalist policies, a paradigm shift akin to foundation models in NLP. She is also the driving force behind **DROID** (108 citations), a massive, in-the-wild robot manipulation dataset that provides the diverse, high-quality data essential for robust policy learning. To make these advances accessible, Le developed **FogROS2-Config**, an open toolkit that intelligently selects cost-effective cloud server configurations for robotics workloads. Her work on automating high-precision tasks like **deformable gasket assembly** further showcases her ability to tackle complex, real-world manufacturing challenges. With her contributions already garnering hundreds of citations, Charlotte Le is a rising star defining the next generation of capable, data-driven robots.

Research Focus

Key Achievements

3
H-Index
5
Papers
236
Total Citations
47
Avg Citations/Paper
🏆 Most Cited Paper
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration<sup>0</sup>
119 citations · 2024
📈 Most Prolific Year: 2024 (5 Papers)
🤝 Key Collaborators: 183
🏛 Institutions: University of California, Berkeley, Institute of Occupational Medicine

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago