用于可扩展机器人模仿学习的增强现实演示
Augmented Reality Demonstrations for Scalable Robot Imitation Learning
AI总结：
本文提出一种基于增强现实的辅助框架，使非专家用户能用HoloLens 2为机器人模仿学习提供演示，实现可扩展的演示收集，并在到达、推、拾取与放置三项任务上验证了真实机器人重播演示的成功执行。
摘要：
机器人模仿学习（IL）是训练机器人执行操作任务的常用方法，通过模仿人类演示来获取技能。然而，其实用性受到限制，因为要求用户接受操作真实机械臂的训练以提供演示。本文提出一种创新解决方案：一个用于演示收集的增强现实（AR）辅助框架，使非机器人专家用户能够使用HoloLens 2等设备为机器人IL制作演示。该框架促进了真实世界任务的可扩展且多样化的演示收集。我们通过在三个经典机器人学任务上的实验验证了该方法：到达、推和拾取与放置。真实机器人在重播通过AR收集的演示时成功执行了每项任务。
英文摘要：
Robot Imitation Learning (IL) is a widely used method for training robots to perform manipulation tasks that involve mimicking human demonstrations to acquire skills. However, its practicality has been limited due to its requirement that users be trained in operating real robot arms to provide demonstrations. This paper presents an innovative solution: an Augmented Reality (AR)-assisted framework for demonstration collection, empowering non-roboticist users to produce demonstrations for robot IL using devices like the HoloLens 2. Our framework facilitates scalable and diverse demonstration collection for real-world tasks. We validate our approach with experiments on three classical robotics tasks: reach, push, and pick-and-place. The real robot performs each task successfully while replaying demonstrations collected via AR.
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。
