To train generalist robot policies, machine learning methods often require a substantial amount of expert human teleoperation data. An ideal robot for humans collecting data is one that closely mimics them: bimanual arms and dexterous hands. However, creating such a bimanual teleoperation system with over 50 DoF is a significant challenge. To address this, we introduce Bidex, an extremely dexterous, low-cost, low-latency and portable bimanual dexterous teleoperation system which relies on motion capture gloves and teacher arms. We compare Bidex to a Vision Pro teleoperation system and a SteamVR system and find Bidex to produce better quality data for more complex tasks at a faster rate. Additionally, we show Bidex operating a mobile bimanual robot for in the wild tasks. The robot hands (5k USD) and teleoperation system (7k USD) is readily reproducible and can be used on many robot arms including two xArms (16k USD). Website at https://bidex-teleop.github.io/

翻译：为训练通用机器人策略，机器学习方法通常需要大量专家人类遥操作数据。理想的机器人数据采集平台应能高度模拟人类操作者：即配备双臂与灵巧手。然而，构建具有超过50个自由度的此类双手机器人遥操作系统存在显著挑战。为此，我们提出Bidex——一套基于动作捕捉手套与示教机械臂的极高灵巧度、低成本、低延迟、便携式双手机器人灵巧遥操作系统。通过将Bidex与Vision Pro遥操作系统及SteamVR系统进行对比，我们发现Bidex能以更快速度为更复杂任务生成更高质量数据。此外，我们展示了Bidex操控移动双手机器人执行野外任务的实例。该机器人灵巧手（5000美元）与遥操作系统（7000美元）具备良好的可复现性，可适配多种机械臂平台，包括两台xArm机械臂（16000美元）。项目网站：https://bidex-teleop.github.io/