Manipulating Highly Deformable Materials Using a Visual Feedback Dictionary
This addresses the challenge of autonomous robotic manipulation of deformable objects, which is incremental as it builds on visual servoing techniques.
The paper tackles the problem of robotic manipulation of highly deformable materials like cloth by introducing a visual feedback dictionary method, achieving successful manipulation across various cloth types and tasks.
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.