Dexterous manipulation is a critical area of robotics. In this field, teleoperation faces three key challenges: user-friendliness for novices, safety assurance, and transferability across different platforms. While collecting real robot dexterous manipulation data by teleoperation to train robots has shown impressive results on diverse tasks, due to the morphological differences between human and robot hands, it is not only hard for new users to understand the action mapping but also raises potential safety concerns during operation. To address these limitations, we introduce TelePhantom. This teleoperation system offers real-time visual feedback on robot actions based on human user inputs, with a total hardware cost of less than $1,000. TelePhantom allows the user to see a virtual robot that represents the outcome of the user's next movement. By enabling flexible switching between command visualization and actual execution, this system helps new users learn how to demonstrate quickly and safely. We demonstrate its superiority over other teleoperation systems across five tasks, emphasize its ease of use, and highlight its ease of deployment across diverse input sensors and robotic platforms. We will release our code and a deployment document on our website: https://telephantom.github.io/.

翻译：灵巧操作是机器人学的关键领域。在该领域中，遥操作面临三大挑战：对新手用户的友好性、安全性保障以及跨平台可迁移性。虽然通过遥操作收集真实机器人灵巧操作数据来训练机器人已在多样化任务中展现出显著成效，但由于人手与机器人手部存在形态差异，新用户不仅难以理解动作映射关系，操作过程中还存在潜在安全隐患。为应对这些局限，我们提出了TelePhantom。该遥操作系统可根据人类用户输入实时提供机器人动作的视觉反馈，总硬件成本低于1000美元。TelePhantom允许用户观察代表其下一步动作执行结果的虚拟机器人。通过实现指令可视化与实际执行间的灵活切换，本系统帮助新用户快速安全地学习演示方法。我们在五项任务中验证了其相对于其他遥操作系统的优越性，着重强调了其易用性，并凸显了其在多样化输入传感器与机器人平台间的易部署特性。我们将在项目网站发布代码及部署文档：https://telephantom.github.io/。