Max Robotics — Global Service Robot Directory + US Certification

About

Chuer Pan is a rising star in robotics, whose work is reshaping how robots learn to manipulate objects in the real world. Her research centers on scalable robot learning, cross-embodiment transfer, and data-efficient policy learning—bridging the gap between controlled lab settings and unstructured, in-the-wild environments. Pan’s most impactful contribution is the **Universal Manipulation Interface (UMI)** , a framework that enables robots to learn complex manipulation skills directly from human demonstrations collected with a simple, hand-held gripper. This work, already garnering over 130 citations, eliminates the need for expensive, in-the-wild robot deployments during data collection. She is also a key contributor to the **Open X-Embodiment** project, a massive collaborative effort that produced a standardized dataset and the RT-X models, which have become foundational resources for the robotics community, accumulating over 220 citations across two publications. Additionally, her work on **TAX-Pose** tackles the fundamental challenge of task-specific pose estimation for manipulating novel objects. Through these contributions, Pan is helping to democratize robot learning, making it more accessible, scalable, and generalizable.