This is the supporting material for the paper "Capability-based Frameworks for Industrial Robot Skills: a Survey". Within this repo the code used to extract information automatically from a review table about skill-taxonomies togheter with supplementary material (i.e., figures) are provided. If you find this work useful please consider citing it.

[2022/06/24] The preprint and this repo have been updated for the final submission.

[2022/05/26] Our paper was accepted for CASE 2022, we are polishing the review for final submission.

[2022/03/01] Arxiv preprint uploaded and CASE 2022 submission.

[2022/02/10] Bibtex of the reviewed papers available.

[2022/02/07] First version of the review with review table has been loaded.

The above graph shows the general clustering of all the identified actions (task, skill, primitive) found during the review. For a better analysis of the results this repo provided links and clustering across the different classes.

For more information on the clusters within primitives visit the README

For more information on the clusters within skills visit the README

For more information on the clusters within tasks visit the README

In data/out/bibtex you can find the list which contains the bibtex entry of the reviewed papers.

The review table containing the raw data is stored under data/in.

For info about the code to extract wordclouds and create clusters visit README.

In order to visualize the different wordclouds, bar plots and supporting images you can visit data/out. Within the folder the data is organized upon all, task, skill and primitive. Moreover, the definition of the requirements is as follows:

• Matteo Pantano - matteopantano
• Thomas Eiband - teiband

@misc{pantano2022capabilitybased,
  title={Capability-based Frameworks for Industrial Robot Skills: a Survey}, 
  author={Matteo Pantano and Thomas Eiband and Dongheui Lee},
  year={2022},
  eprint={2203.00538},
  archivePrefix={arXiv},
  primaryClass={cs.RO}
}