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
Top Papers
- 1
- 2DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset108 citations · 2024
- 3
- 4DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset3 citations · 2024
- 5Automating Deformable Gasket Assembly2 citations · 2024