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Information exchange design patterns for robot swarm foraging and their application in robot control algorithms

Information exchange design patterns for robot swarm foraging and their application in robot control algorithms
Information exchange design patterns for robot swarm foraging and their application in robot control algorithms
In swarm robotics, a design pattern provides high-level guidelines for the implementation of a particular robot behaviour and describes its impact on swarm performance. In this paper, we explore information exchange design patterns for robot swarm foraging. First, a method for the specification of design patterns for robot swarms is proposed that builds on previous work in this field and emphasises modular behaviour design, as well as information-centric micro-macro link analysis. Next, design pattern application rules that can facilitate the pattern usage in robot control algorithms are given. A catalogue of six design patterns is then presented. The patterns are derived from an extensive list of experiments reported in the swarm robotics literature, demonstrating the capability of the proposed method to identify distinguishing features of robot behaviour and their impact on swarm performance in a wide range of swarm implementations and experimental scenarios. Each pattern features a detailed description of robot behaviour and its associated parameters, facilitated by the usage of a multi-agent modeling language, BDRML, and an account of feedback loops and forces that affect the pattern’s applicability. Scenarios in which the pattern has been used are described. The consequences of each design pattern on overall swarm performance are characterised within the Information-Cost-Reward framework, that makes it possible to formally relate the way in which robots acquire, share and utilise information. Finally, the patterns are validated by demonstrating how they improved the performance of foraging e-puck swarms and how they could guide algorithm design in other scenarios.
Pitonakova, Lenka
ef806152-a9c0-4075-806d-c75f0d3f7bbb
Crowder, Richard
ddeb646d-cc9e-487b-bd84-e1726d3ac023
Bullock, Seth
2ad576e4-56b8-4f31-84e0-51bd0b7a1cd3
Pitonakova, Lenka
ef806152-a9c0-4075-806d-c75f0d3f7bbb
Crowder, Richard
ddeb646d-cc9e-487b-bd84-e1726d3ac023
Bullock, Seth
2ad576e4-56b8-4f31-84e0-51bd0b7a1cd3

Pitonakova, Lenka, Crowder, Richard and Bullock, Seth (2018) Information exchange design patterns for robot swarm foraging and their application in robot control algorithms. Frontiers in Robotics and AI, 5. (doi:10.3389/frobt.2018.00047).

Record type: Article

Abstract

In swarm robotics, a design pattern provides high-level guidelines for the implementation of a particular robot behaviour and describes its impact on swarm performance. In this paper, we explore information exchange design patterns for robot swarm foraging. First, a method for the specification of design patterns for robot swarms is proposed that builds on previous work in this field and emphasises modular behaviour design, as well as information-centric micro-macro link analysis. Next, design pattern application rules that can facilitate the pattern usage in robot control algorithms are given. A catalogue of six design patterns is then presented. The patterns are derived from an extensive list of experiments reported in the swarm robotics literature, demonstrating the capability of the proposed method to identify distinguishing features of robot behaviour and their impact on swarm performance in a wide range of swarm implementations and experimental scenarios. Each pattern features a detailed description of robot behaviour and its associated parameters, facilitated by the usage of a multi-agent modeling language, BDRML, and an account of feedback loops and forces that affect the pattern’s applicability. Scenarios in which the pattern has been used are described. The consequences of each design pattern on overall swarm performance are characterised within the Information-Cost-Reward framework, that makes it possible to formally relate the way in which robots acquire, share and utilise information. Finally, the patterns are validated by demonstrating how they improved the performance of foraging e-puck swarms and how they could guide algorithm design in other scenarios.

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Accepted/In Press date: 11 April 2018
e-pub ahead of print date: 7 June 2018
Published date: 7 June 2018

Identifiers

Local EPrints ID: 421411
URI: https://eprints.soton.ac.uk/id/eprint/421411
PURE UUID: e2fc0732-5aad-4527-86fd-22282028fc92
ORCID for Lenka Pitonakova: ORCID iD orcid.org/0000-0003-3633-7302

Catalogue record

Date deposited: 11 Jun 2018 16:30
Last modified: 13 Aug 2018 16:31

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Contributors

Author: Lenka Pitonakova ORCID iD
Author: Richard Crowder
Author: Seth Bullock

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