Shaukat, N., Dubey, S. orcid.org/0000-0002-7365-8474, Kaddouh, B. et al. (8 more authors) (2024) Trustworthy ROS software architecture for autonomous drones missions: from RoboChart modelling to ROS implementation. In: IEEE/ASME International Conference on Mechtronic and Embedded Systems and Applications (MESA). 2024 20th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA), 02-04 Sep 2024, Genova, Italy. Institute of Electrical and Electronics Engineers (IEEE) ISBN 979-8-3315-1624-6
Abstract
Drones are becoming essential tools in emergency situations such as search and rescue, surveillance, and firefighting. These applications make the development of trustworthy software a priority to increase efficiency, cut costs, and reduce risks, in future replacing human personnel in challenging areas. RoboChart, a platform-agnostic tool, brings numerous benefits to the robotics community by providing a language and high-level tool to describe a model via automatic verification and exhaustive testing of the model. However, when it comes to real robotics it is essential to use testing tools suitable for specific robotic software. In the context of the Robotic Operating System (ROS), it imposes its own design constraints, best practices, and communication requirements. This paper aims to apply the RoboChart modelling approach to autonomous firefighting drones, putting forward a low-level ROS software architecture that aligns with RoboChart models, ensuring the trustworthiness of the system during operation.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 IEEE. |
Keywords: | Information and Computing Sciences; Artificial Intelligence; Software Engineering |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > School of Mechanical, Aerospace and Civil Engineering |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 Nov 2024 12:29 |
Last Modified: | 05 Nov 2024 12:39 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/mesa61532.2024.10704818 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:219249 |