OPEN TEACH：一种面向机器人操作的通用遥操作系统
OPEN TEACH: A Versatile Teleoperation System for Robotic Manipulation
AI总结：
针对现有机器人遥操作数据采集平台专有、昂贵且适配性差的问题，研究团队提出基于Meta Quest 3的开源通用遥操作系统OPEN TEACH，支持多类机器人实时控制，操作性能更优且采集数据可用于策略学习。
摘要：
开源且用户友好的工具是各学科科学进步的基石。数据驱动学习的广泛应用已在多指灵巧操作、双臂操作以及从物流到家庭机器人的各类应用中取得了显著进展。然而，现有数据采集平台通常是专有的、成本高昂，或是为特定机器人形态定制的。我们提出了OPEN TEACH，这是一款新型遥操作系统，利用VR头显将用户沉浸在混合现实中，以实现直观的机器人控制。OPEN TEACH基于售价500美元的高性价比Meta Quest 3构建，通过一款易用的应用程序，可对包括多指手和双臂机械臂在内的多种机器人进行实时控制。借助自然的手部手势和动作，用户能以最高90Hz的频率操控机器人，同时获得流畅的视觉反馈，界面控件还可提供环境的特写视图。我们在不同机器人上的38项任务中验证了OPEN TEACH的通用性。一项全面的用户研究表明，其遥操作能力较AnyTeleop框架有显著提升。进一步实验显示，采集的数据可适配10项灵巧且接触丰富的操作任务的策略学习。目前OPEN TEACH支持Franka、xArm、Jaco和Allegro平台，且已完全开源以推动更广泛的应用。相关视频可访问https://open-teach.github.io/查看。
英文摘要：
Open-sourced, user-friendly tools form the bedrock of scientific advancement across disciplines. The widespread adoption of data-driven learning has led to remarkable progress in multi-fingered dexterity, bimanual manipulation, and applications ranging from logistics to home robotics. However, existing data collection platforms are often proprietary, costly, or tailored to specific robotic morphologies. We present OPEN TEACH, a new teleoperation system leveraging VR headsets to immerse users in mixed reality for intuitive robot control. Built on the affordable Meta Quest 3, which costs $500, OPEN TEACH enables real-time control of various robots, including multi-fingered hands and bimanual arms, through an easy-to-use app. Using natural hand gestures and movements, users can manipulate robots at up to 90Hz with smooth visual feedback and interface widgets offering closeup environment views. We demonstrate the versatility of OPEN TEACH across 38 tasks on different robots. A comprehensive user study indicates significant improvement in teleoperation capability over the AnyTeleop framework. Further experiments exhibit that the collected data is compatible with policy learning on 10 dexterous and contact-rich manipulation tasks. Currently supporting Franka, xArm, Jaco, and Allegro platforms, OPEN TEACH is fully open-sourced to promote broader adoption. Videos are available at https://open-teach.github.io/.
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。
