Cloud robotics platforms: review and comparative analysis

Dawarka, Viraj and Bekaroo, Girish ORCID: https://orcid.org/0000-0003-1753-4300 (2018) Cloud robotics platforms: review and comparative analysis. Proceedings 2018 International Conference on Intelligent and Innovative Computing Applications. In: ICONIC: MAURICON 2018 International Conference on Intelligent and Innovative Computing Applications, 06-07 Dec 2018, Plaine Magnien, Mauritius. e-ISBN 9781538664773, pbk-ISBN 9781538664780. (doi:10.1109/ICONIC.2018.8601220)

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Abstract

Due to the various advantages that the cloud can offer to robots, there has been the recent emergence of the cloud robotics paradigm. Cloud robotics permits robots to unload computing and storage related tasks into the cloud, and as such, robots can be built with smaller on-board computers. The use of cloud-robotics also allows robots to share knowledge within the community over a dedicated cloud space. In order to build-up robots that benefit from the cloud-robotics paradigm, different cloud-robotics platforms have been released during recent years. This paper critically reviews and compares existing cloud robotic platforms in order to provide recommendations on future use and gaps that still need to be addressed. To achieve this, 8 cloud robotic platforms were investigated. Key findings reveal varying underlying architectures and models adopted by these platforms, in addition to different features offered to end-users.

Item Type: Conference or Workshop Item (Paper)
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 29769
Notes on copyright: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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Depositing User: Girish Bekaroo
Date Deposited: 26 May 2020 14:41
Last Modified: 29 May 2020 12:54
URI: https://eprints.mdx.ac.uk/id/eprint/29769

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