开源遥操作框架，支持任意机械臂、手型和输入设备的高精度数据采集。
Open TeleDex: A Hardware-Agnostic Teleoperation System for Imitation Learning based Dexterous Manipulation
- 统一框架兼容任意机器人臂、灵巧手和输入设备，解决异构设备数据采集难题。
- 提出新型手部姿态重定向算法，显著提升不同设备间的兼容性与精度。
- 提供公开高质量数据集，助力学术与工业界复杂抓取任务研究。
精确且高保真的演示数据采集是部署机器人模仿学习系统的关键瓶颈，尤其在面对异构机器人平台时。现有遥操作系统往往无法在多种遥操作设备间保证高精度数据采集。为此，我们开发了 Open TeleDex，一个专为演示数据采集设计的统一遥操作框架。Open TeleDex 特别解决了 TripleAny 挑战，无缝支持任意机械臂、任意灵巧手和任意外部输入设备。此外，我们提出一种新颖的手部姿态重定向算法，显著提升了 Open TeleDex 的互操作性，使其能稳健且准确地适配更广泛的异构主从设备组合。Open TeleDex 构建了一个基础性、高质量且公开可用的平台，旨在加速复杂机器人操作与模仿学习领域的学术研究和产业发展。
原文摘要 · Abstract (English)
Accurate and high-fidelity demonstration data acquisition is a critical bottleneck for deploying robot Imitation Learning (IL) systems, particularly when dealing with heterogeneous robotic platforms. Existing teleoperation systems often fail to guarantee high-precision data collection across diverse types of teleoperation devices. To address this, we developed Open TeleDex, a unified teleoperation framework engineered for demonstration data collection. Open TeleDex specifically tackles the TripleAny challenge, seamlessly supporting any robotic arm, any dexterous hand, and any external input device. Furthermore, we propose a novel hand pose retargeting algorithm that significantly boosts the interoperability of Open TeleDex, enabling robust and accurate compatibility with an even wider spectrum of heterogeneous master and slave equipment. Open TeleDex establishes a foundational, high-quality, and publicly available platform for accelerating both academic research and industry development in complex robotic manipulation and IL.
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