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README.md

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 # GaTORS: A Game-Theoretic Tool for Optimal Robot Selection and Design in Surface Coverage Applications
 
+[![github.io](https://img.shields.io/badge/github.io-MainPage-black.svg)](https://utnuclearroboticspublic.github.io/gators/)
+
 ![](images/i3.png)
 
 ## About

docs/README.md

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+# GaTORS: A Game-Theoretic Tool for Optimal Robot Selection and Design
+
+#### Steven Swanbeck, Daniel Meza, Jared Rosenbaum, David Fridovich-Keil, and Mitch Pryor
+
+## Submitted to IROS 2024
+<!-- --- -->
+
+<!-- {% include youtube.html id="fjWK2SCbFZ8" %} -->
+
+### About
+As the number of commercially-available robots
+increases, users face the challenge of evaluating many options
+to identify the optimal system for their needs. This market
+saturation also compels providers to ensure new systems are
+competitive with or superior to existing robots to increase
+economic viability. The need for evaluation extends to multi-
+robot teams collaborating toward shared objectives, where
+understanding individual contributions to overall team per-
+formance is complex but necessary. One specific application
+domain for robot platform selection in industry is autonomous
+surface coverage, which includes tasks such as painting, clean-
+ing, and surveying in industrial facilities. To assist in the
+design and selection of robotic systems for surface coverage
+applications, we introduce GaTORS, a novel tool that frames
+the surface coverage task allocation process as a collaborative
+general-sum discrete-time game. By parameterizing robots with
+a set of common constraints, this tool enables performance
+evaluation of existing and potential future robotic systems.
+GaTORS is evaluated in a case study of surface coverage for
+corrosion mitigation in an industrial refinery, with experiments
+demonstrating its utility in selecting existing robotic platforms
+best suited to complete the specific coverage task. These
+experiments also highlight GaTORS’ potential to inform the
+design of new systems that can efficiently accomplish assigned
+tasks within practical time and cost constraints. Due to its
+flexibility, GaTORS can be easily adapted to provide similar
+insights for other types of robots in different environments and
+surface coverage applications.
+
+
+<!-- ### Citation
+```
+@inproceedings{regalswanbeckARSTARAugmentedReality2024,
+  title = {AR-STAR: An Augmented Reality Tool for Online Modification of Robot Point Cloud Data},
+  author = {Regal, Frank and Swanbeck, Steven and Parra, Fabian and Pryor, Mitch},
+  booktitle = {HRI '24 Companion},
+  eventtitle = {ACM/IEEE International Conference on Human-Robot Interaction (HRI)},
+  publisher = {ACM},
+  isbn = {979-8-4007-0323-2/24/03},
+  doi = {10.1145/3610978.3640571},
+  year = {2024},
+  location = {Boulder, CO}
+}
+``` -->

docs/_config.yml

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+plugins:
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+title: "GaTORS: A Game-Theoretic Tool for Optimal Robot Selection and Design"
+description: "Supplemental Material"
+show_downloads: false

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models/clouds/info.txt

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+Clouds should go in this directory!