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-# FastUMI-100K: Advancing Data-Driven Robotic Manipulation with a Large-Scale UMI-Style Dataset
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-## [[paper](https://arxiv.org/abs/2510.08022)]      [[dataset](https://huggingface.co/datasets/IPEC-COMMUNITY/FastUMI_100k_lerobot)]
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+# 🚀 FastUMI-100K: Advancing Data-Driven Robotic Manipulation
 
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-  <img alt="teaser figure" src="./paper.png" width="100%">
+  <a href="https://arxiv.org/abs/2510.08022"><img src="https://img.shields.io/badge/arXiv-2510.08022-b31b1b.svg" alt="Paper"></a>
+  <a href="https://huggingface.co/datasets/IPEC-COMMUNITY/FastUMI_100k_lerobot"><img src="https://img.shields.io/badge/Dataset-FastUMI--100K-blue" alt="Dataset"></a>
+  <img src="https://img.shields.io/badge/License-Apache--2.0-green" alt="License">
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+<img alt="teaser figure" src="./paper.png" width="100%">
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 ## Overview
 FastUMI-100K is a large-scale, high-quality UMI-style dataset designed for data-driven robotic manipulation learning. Featuring over **100K+ demonstration trajectories** across **54 diverse tasks** and hundreds of object types, the dataset provides multi-view wrist-mounted fisheye images and high-frequency end-effector states. To facilitate seamless integration with modern robot learning frameworks, all data has been standardized into the **LeRobot v2.1** format.