The complex physical properties of highly deformable materials such as clothes pose significant challenges fanipulation systems. We present a novel visual feedback dictionary-based method for manipulating defoor autonomous robotic mrmable objects towards a desired configuration. Our approach is based on visual servoing and we use an efficient technique to extract key features from the RGB sensor stream in the form of a histogram of deformable model features. These histogram features serve as high-level representations of the state of the deformable material. Next, we collect manipulation data and use a visual feedback dictionary that maps the velocity in the high-dimensional feature space to the velocity of the robotic end-effectors for manipulation. We have evaluated our approach on a set of complex manipulation tasks and human-robot manipulation tasks on different cloth pieces with varying material characteristics.
@article{arxiv.1710.06947,
title = {Manipulating Highly Deformable Materials Using a Visual Feedback Dictionary},
author = {Biao Jia and Zhe Hu and Jia Pan and Dinesh Manocha},
journal= {arXiv preprint arXiv:1710.06947},
year = {2019}
}