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A Modular Cloud Robotics Architecture for Data Management and Mission Handling of Unmanned Robotic Services

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Advances in Service and Industrial Robotics (RAAD 2017)

Part of the book series: Mechanisms and Machine Science ((Mechan. Machine Science,volume 49))

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Abstract

Many human service robotics applications are looking to cloud robotics as a possible paradigm in which robots, seen as remote and autonomous agents, have the possibility to connect to a common network and share information and knowledge they gather from real world on a complex and powerful data infrastructure. Conversely, they (the robots) can also consume data collected by other agents or made available on accessible database and repositories. In this paper, we propose a possible management of different services, exploiting the possibilities offered by cloud robotics in a complex scenario (smart city, smart agriculture, search & rescue). A high-level cloud platform manages several unmanned robots (UAVs and UGVs) with the goal of providing support to the end users that require it via a remote connection (web, SSH, VPN, etc.). The robots are used in the operating area while forwarding real-time data and video streaming to the final users, connected to the same cloud platform, that can manage them by remote.

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Acknowledgments

The authors wish to thank TIM Telecom Italia for the collaboration in the Fly4SmartCity project [2] and PROS3 [17] for the strong support on the UAV robotic platforms, the MicroPilot autopilot and some of the described application scenarios.

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Correspondence to Marcello Chiaberge .

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Silvagni, M., Chiaberge, M., Sanguedolce, C., Dara, G. (2018). A Modular Cloud Robotics Architecture for Data Management and Mission Handling of Unmanned Robotic Services. In: Ferraresi, C., Quaglia, G. (eds) Advances in Service and Industrial Robotics. RAAD 2017. Mechanisms and Machine Science, vol 49. Springer, Cham. https://doi.org/10.1007/978-3-319-61276-8_55

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  • DOI: https://doi.org/10.1007/978-3-319-61276-8_55

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61275-1

  • Online ISBN: 978-3-319-61276-8

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