Inverted ant colony optimization for search and rescue in an unknown maze-like indoor environment

Zainab Husain, Dymitr Ruta, Fabrice Sare, Yousof Al-Hammadi, A. F. Isakovic

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

We demonstrate the applicability of inverted Ant Colony Optimization (iACO) for target search in a complex unknown indoor environment simulated by a maze. e colony of autonomous ants lay repellent pheromones to speed up exploration of the unknown maze instead of reinforcing presence in already visited areas. e role of a target-collocated beacon signal within the maze is evaluated in terms of its utility to guide the search. Variants of iACO were developed, with beacon initialization (iACO-B), and with increased sensing ranges (iACO-R with a 2-step far-sightedness) to quantify the most eective one. e presented models can be implemented with self-organizing wireless sensor networks carried by autonomous drones or vehicles and can oer life-saving services of localizing victims of natural disasters or during major infrastructure failures.

Original languageBritish English
Title of host publicationGECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion
Pages89-90
Number of pages2
ISBN (Electronic)9781450357647
DOIs
StatePublished - 6 Jul 2018
Event2018 Genetic and Evolutionary Computation Conference, GECCO 2018 - Kyoto, Japan
Duration: 15 Jul 201819 Jul 2018

Publication series

NameGECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion

Conference

Conference2018 Genetic and Evolutionary Computation Conference, GECCO 2018
Country/TerritoryJapan
CityKyoto
Period15/07/1819/07/18

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