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Autonomous Robots

Erschienen in:

16.05.2019

SOUL: data sharing for robot swarms

verfasst von: Vivek Shankar Varadharajan, David St-Onge, Bram Adams, Giovanni Beltrame

Erschienen in: Autonomous Robots | Ausgabe 3-4/2020

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Abstract

Interconnected devices and mobile multi-robot systems are increasingly present in many real-life scenarios. To be effective, these systems need to collect large amounts of data from their environment, and often these data need to be aggregated, shared, and distributed. Many multi-robot systems are designed to share state information and commands, but their communication infrastructure is often too limited for significant data transfers. This paper introduces Swarm-Oriented Upload of Labeled data, a mechanism that allows members of a fully distributed system to share data with their peers. We leverage a BitTorrent-like strategy to share data in smaller chunks, or datagrams, with policies that minimize reconstruction time. We performed extensive simulations to study the properties of the system and to demonstrate its scalability. We report experiments conducted with real robots following two realistic deployment scenarios: searching for objects in a scene, and replacing the full identity of a defective robot.

Vorheriger Artikel Gaussian process decentralized data fusion meets transfer learning in large-scale distributed cooperative perception

Nächster Artikel A robust localization system for multi-robot formations based on an extension of a Gaussian mixture probability hypothesis density filter

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https://github.com/vivek-shankar/SOUL.git.

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Titel: SOUL: data sharing for robot swarms
verfasst von: Vivek Shankar Varadharajan
David St-Onge
Bram Adams
Giovanni Beltrame
Publikationsdatum: 16.05.2019
Verlag: Springer US
Erschienen in: Autonomous Robots / Ausgabe 3-4/2020
Print ISSN: 0929-5593
Elektronische ISSN: 1573-7527
DOI: https://doi.org/10.1007/s10514-019-09855-2

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