Surveillance Task Optimized by Evolutionary Shared Tabu Inverted Ant Cellular Automata Model for Swarm Robotics Navigation Control

Lopes, Hamilton Junior Mendes; Lima, Danielli A.

doi:10.2139/ssrn.3962774

Cited by 1 publication

(1 citation statement)

References 49 publications

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“…Ref. [24] proposed a new hybrid method that combines natural and evolutionary computing methods, using genetic algorithms, inverted ant pheromones, and Tabu Search to implement the swarm robots in surveillance tasks. The new model is named Genetic Shared Tabu Inverted Ant Cellular.…”

Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%

A Survey on Swarm Robotics for Area Coverage Problem

Muhsen,

Sadiq,

Raheem

2023

Algorithms

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The area coverage problem solution is one of the vital research areas which can benefit from swarm robotics. The greatest challenge to the swarm robotics system is to complete the task of covering an area effectively. Many domains where area coverage is essential include exploration, surveillance, mapping, foraging, and several other applications. This paper introduces a survey of swarm robotics in area coverage research papers from 2015 to 2022 regarding the algorithms and methods used, hardware, and applications in this domain. Different types of algorithms and hardware were dealt with and analysed; according to the analysis, the characteristics and advantages of each of them were identified, and we determined their suitability for different applications in covering the area for many goals. This study demonstrates that naturally inspired algorithms have the most significant role in swarm robotics for area coverage compared to other techniques. In addition, modern hardware has more capabilities suitable for supporting swarm robotics to cover an area, even if the environment is complex and contains static or dynamic obstacles.

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Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%