EasyMimic: 一种低成本的机器人模仿学习框架
EasyMimic: A Low-Cost Framework for Robot Imitation Learning from Human Videos
AI总结：
EasyMimic通过低成本框架实现机器人从人类视频快速学习操控策略，减少对昂贵数据的依赖，推动家庭机器人发展。
摘要：
机器人模仿学习通常受到收集大规模真实世界数据成本高的限制。这一挑战对低成本的家庭用机器人尤其显著，因为它们必须既用户友好又经济。为此，我们提出了EasyMimic框架，一种低成本且可复制的解决方案，使机器人能够快速从人类视频演示中学习操控策略。我们的方法首先从视频中提取3D手轨迹。一个动作对齐模块然后将这些轨迹映射到低成本机器人的抓取控制空间。为了弥合人类到机器人的领域差距，我们引入了一种简单且用户友好的手部视觉增强策略。然后我们使用协同训练方法，在处理过的人类数据和少量机器人数据上微调模型，从而快速适应新任务。在低成本LeRobot平台上进行的实验表明，EasyMimic在各种操控任务中均能实现高性能。它显著减少了对昂贵机器人数据收集的依赖，为将智能机器人带入家庭提供了一条实用路径。项目网站：https://zt375356.github.io/EasyMimic-Project/。
英文摘要：
Robot imitation learning is often hindered by the high cost of collecting large-scale, real-world data. This challenge is especially significant for low-cost robots designed for home use, as they must be both user-friendly and affordable. To address this, we propose the EasyMimic framework, a low-cost and replicable solution that enables robots to quickly learn manipulation policies from human video demonstrations captured with standard RGB cameras. Our method first extracts 3D hand trajectories from the videos. An action alignment module then maps these trajectories to the gripper control space of a low-cost robot. To bridge the human-to-robot domain gap, we introduce a simple and user-friendly hand visual augmentation strategy. We then use a co-training method, fine-tuning a model on both the processed human data and a small amount of robot data, enabling rapid adaptation to new tasks. Experiments on the low-cost LeRobot platform demonstrate that EasyMimic achieves high performance across various manipulation tasks. It significantly reduces the reliance on expensive robot data collection, offering a practical path for bringing intelligent robots into homes. Project website: https://zt375356.github.io/EasyMimic-Project/.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
