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

• URL: http://arxiv.org/abs/2402.14795v2
• Date: Fri, 1 Mar 2024 19:53:57 GMT
• Title: CyberDemo: Augmenting Simulated Human Demonstration for Real-World Dexterous Manipulation
• Authors: Jun Wang, Yuzhe Qin, Kaiming Kuang, Yigit Korkmaz, Akhilan Gurumoorthy, Hao Su, Xiaolong Wang
• Abstract summary: CyberDemo is a novel approach to robotic imitation learning that leverages simulated human demonstrations for real-world tasks. Our research demonstrates the significant potential of simulated human demonstrations for real-world dexterous manipulation tasks.
• Score: 27.069114421842045
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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

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