research-article

Energy-efficient environment mapping via evolutionary algorithm optimized multi-agent localization

Authors:

Stephan Schlupkothen,

Giovanni Iacca,

Gerd AscheidAuthors Info & Claims

GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion

Pages 1721 - 1726

https://doi.org/10.1145/3067695.3084201

Published: 15 July 2017 Publication History

Abstract

Miniature autonomous sensory agents (MASA) can play a profound role in the exploration of hardly accessible unknown environments, thus, impacting many applications such as monitoring of underground infrastructure or exploration for natural resources, e.g. oil and gas, or even human body diagnostic exploration. However, using MASA presents a wide range of challenges due to limitations of the available hardware resources caused by their scaled-down size. Consequently, these agents are kinetically passive, i.e. they cannot be guided through the environment. Furthermore, their communication range and rate is limited, which affects the quality of localization and, consequently, mapping. In addition, conducting real-time localization and mapping is not possible. As a result, Simultaneous Localization and Mapping (SLAM) techniques are not suitable and a new problem definition is needed. In this paper we introduce what we dub as the Centralized Offline Localization And Mapping (COLAM) problem, highlighting its key elements, then we present a model to solve it. In this model evolutionary algorithms (EAs) are used to optimize agents' resources off-line for an energy-efficient environment mapping. Furthermore, we illustrate a modified version of Vietoris-Rips Complex we dub as Trajectory Incorporated Vietoris-Rips (TIVR) complex as a tool to conduct mapping. Finally, we project the proposed model on real experiments and present results.

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Cited By

Hallawa AIacca GSariman CRahman TCochez MAscheid G(2020)Morphological evolution for pipe inspection using Robot Operating System (ROS)Materials and Manufacturing Processes10.1080/10426914.2020.174633535:6(714-724)Online publication date: 7-May-2020
https://doi.org/10.1080/10426914.2020.1746335
Schlupkothen SHallawa AAscheid G(2018)Evolutionary Algorithm Optimized Centralized Offline Localization and Mapping2018 International Conference on Computing, Networking and Communications (ICNC)10.1109/ICCNC.2018.8390410(625-631)Online publication date: Mar-2018
https://doi.org/10.1109/ICCNC.2018.8390410

Index Terms

Energy-efficient environment mapping via evolutionary algorithm optimized multi-agent localization
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Sensor networks
2. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Bio-inspired approaches
        Evolvable hardware

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cover image ACM Conferences

GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion

July 2017

1934 pages

ISBN:9781450349390

DOI:10.1145/3067695

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 July 2017

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European Union

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GECCO '17

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SIGEVO

GECCO '17: Genetic and Evolutionary Computation Conference

July 15 - 19, 2017

Berlin, Germany

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Hallawa AIacca GSariman CRahman TCochez MAscheid G(2020)Morphological evolution for pipe inspection using Robot Operating System (ROS)Materials and Manufacturing Processes10.1080/10426914.2020.174633535:6(714-724)Online publication date: 7-May-2020
https://doi.org/10.1080/10426914.2020.1746335
Schlupkothen SHallawa AAscheid G(2018)Evolutionary Algorithm Optimized Centralized Offline Localization and Mapping2018 International Conference on Computing, Networking and Communications (ICNC)10.1109/ICCNC.2018.8390410(625-631)Online publication date: Mar-2018
https://doi.org/10.1109/ICCNC.2018.8390410

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