In this paper, we present a multimodal mobile teleoperation system that consists of a novel vision-based hand pose regression network (Transteleop) and an IMU-based arm tracking method. Transteleop observes the human hand through a low-cost depth camera and generates not only joint angles but also depth images of paired robot hand poses through an image-to-image translation process. A keypoint-based reconstruction loss explores the resemblance in appearance and anatomy between human and robotic hands and enriches the local features of reconstructed images. A wearable camera holder enables simultaneous hand-arm control and facilitates the mobility of the whole teleoperation system. Network evaluation results on a test dataset and a variety of complex manipulation tasks that go beyond simple pick-and-place operations show the efficiency and stability of our multimodal teleoperation system.
@article{arxiv.2003.05212,
title = {A Mobile Robot Hand-Arm Teleoperation System by Vision and IMU},
author = {Shuang Li and Jiaxi Jiang and Philipp Ruppel and Hongzhuo Liang and Xiaojian Ma and Norman Hendrich and Fuchun Sun and Jianwei Zhang},
journal= {arXiv preprint arXiv:2003.05212},
year = {2020}
}