CyberDemo：增强模拟人类演示以实现现实世界的熟练操作

CyberDemo: Augmenting Simulated Human Demonstration for Real-World Dexterous Manipulation

February 22, 2024

作者: Jun Wang, Yuzhe Qin, Kaiming Kuang, Yigit Korkmaz, Akhilan Gurumoorthy, Hao Su, Xiaolong Wang

cs.AI

摘要

我们介绍了CyberDemo，这是一种新颖的机器人模仿学习方法，利用模拟人类演示来完成真实世界任务。通过在模拟环境中进行大量数据增强，CyberDemo在转移到真实世界时优于传统的同领域真实世界演示，能够处理多样的物理和视觉条件。尽管在数据收集方面具有经济实惠和便利性，CyberDemo在各种任务的成功率方面优于基准方法，并展现出对以前未见过物体的泛化能力。例如，它可以旋转新颖的四阀和五阀，尽管人类演示仅涉及三阀。我们的研究展示了模拟人类演示在真实世界灵巧操作任务中的重要潜力。更多详细信息请访问https://cyber-demo.github.io。

English

We introduce CyberDemo, a novel approach to robotic imitation learning that leverages simulated human demonstrations for real-world tasks. By incorporating extensive data augmentation in a simulated environment, CyberDemo outperforms traditional in-domain real-world demonstrations when transferred to the real world, handling diverse physical and visual conditions. Regardless of its affordability and convenience in data collection, CyberDemo outperforms baseline methods in terms of success rates across various tasks and exhibits generalizability with previously unseen objects. For example, it can rotate novel tetra-valve and penta-valve, despite human demonstrations only involving tri-valves. Our research demonstrates the significant potential of simulated human demonstrations for real-world dexterous manipulation tasks. More details can be found at https://cyber-demo.github.io