David Blanco-Mulero, Yifei Dong, Julia Borras, Florian T. Pokorny, Carme Torras
Under review
Preprint | Dataset
Robotic grasp and manipulation taxonomies, inspired by observing human manipulation strategies, can provide key guidance for tasks ranging from robotic gripper design to the development of manipulation algorithms. The existing grasp and manipulation taxonomies, however, often assume object rigidity, which limits their ability to reason about the complex interactions in the robotic manipulation of deformable objects. Hence, to assist in tasks involving deformable objects, taxonomies need to capture more comprehensively the interactions inherent in deformable object manipulation.
To this end, we introduce T-DOM, a taxonomy that analyses key aspects involved in the manipulation of deformable objects, such as robot motion, forces, prehensile and non-prehensile interactions and, for the first time, a detailed classification of object deformations. To evaluate T-DOM, we curate a dataset of ten tasks involving a variety of deformable objects, such as garments, ropes, and surgical gloves, as well as diverse types of deformations. We analyse the proposed tasks comparing the T-DOM taxonomy with previous well established manipulation taxonomies. Our analysis demonstrates that T-DOM can effectively distinguish between manipulation skills that were not identified in other taxonomies, across different deformable objects and manipulation actions, offering new categories to characterize a skill. The proposed taxonomy significantly extends past work, providing a more fine-grained classification that can be used to describe the robotic manipulation of deformable objects. This work establishes a foundation for advancing deformable object manipulation, bridging theoretical understanding and practical implementation in robotic systems.
Content
The proposed taxonomy is composed of deformation (D), motion (M), and interactions. The interactions are classified as prehensile grasp (G) and non-prehensile interactions (NP), and contact sliding (CS) as a special case of interaction that can take place in both prehensile grasps as well as each sub-category of non-prehensile interactions, shown by a dashed line connecting the CS block. Each sub-category is shown with its associated short tag.
The taxonomy classifies the robotic manipulation of multiple deformable objects showing compression, tension, bending, torsion and shear deformation, as well as combination of these deformations.
Our work proposes a qualitative classification for bending deformation as structured or unstructured for 1D and 2D deformable objects.
The structured level is classified by loops and g-folds, for 1D and 2D objects, respectively.
The unstructured level is classified by knots for 1D objects, and as the number of accessible corners for a cloth flattening task.
We record our dataset using towels, silicone meat phantoms, bags, surgical gowns and gloves. The dataset is composed by RGB and depth images at each timestep of the manipulation, using both UR5 manipulators and hand-held grippers.
Our dataset consists of the following:
Task 1: Fold Towel.
Task 2: Transport Towel.
Task 3: Wring out Towel.
Task 4: Cloth Edge Tracing.
Task 5: Transport Meat.
Task 6: Cloth Flattening.
Task 7: Unfold Medical Gown.
Task 8: Bag Opening and Item Insertion.
Task 9: Open Surgical Glove.
Task 10: Cable Looping.
Below we provide the action segmentation for all the tasks as well as the classification of each transition using T-DOM, Bullock's taxonomy and Paulius' taxonomy.
Júlia Borràs
Institut de Robòtica i Informàtica Industrial, CSIC-UPC
Spain
To cite this work, please use the following BibTex entry:
@article{blancomulero2024tdom,
title={T-DOM: A Taxonomy for Robotic Manipulation of Deformable Objects},
author={David Blanco-Mulero and Yifei Dong and Julia Borras and Florian T. Pokorny and Carme Torras},
year={2024},
eprint={2412.20998},
archivePrefix={arXiv},
primaryClass={cs.RO},
url={https://arxiv.org/abs/2412.20998},
journal={arXiv preprint arXiv:2412.20998},
}