In this work, we present a PICO-based robot remote operating framework that enables low-cost, real-time acquisition of hand motion and pose data, outperforming mainstream visual tracking and motion capture solutions in terms of cost-effectiveness. The framework is natively compatible with the RealMirror ecosystem, offering ready-to-use functionality for stable and precise robotic trajectory recording within the Isaac simulation environment, thereby facilitating the construction of Vision-Language-Action (VLA) datasets. Additionally, the system supports real-time teleoperation of a variety of end-effector-equipped robots, including dexterous hands and robotic grippers. This work aims to lower the technical barriers in the study of upper-limb robotic manipulation, thereby accelerating advancements in VLA-related research.
@article{arxiv.2511.08865,
title = {MirrorLimb: Implementing hand pose acquisition and robot teleoperation based on RealMirror},
author = {Cong Tai and Hansheng Wu and Haixu Long and Zhengbin Long and Zhaoyu Zheng and Haodong Xiang and Tao Shen},
journal= {arXiv preprint arXiv:2511.08865},
year = {2025}
}