A Bacterial Chemotaxis-Inspired Coordination Strategy for Coverage and Aggregation of Swarm Robots

Jiang, Laihao; Mo, Hongwei; Tian, Peng

doi:10.3390/app11031347

Cited by 6 publications

(3 citation statements)

References 35 publications

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“…Ref. [42] introduced a new proposal for a swarm robotic system called a bacterial chemotaxis-inspired coordination strategy (BCCS) for coverage and aggregation. Chaotic preprocessing is used to initialise the starting positions of the robots.…”

Section: Bacterial Foraging Optimisation (Bfo) Algorithmmentioning

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: Bacterial Foraging Optimisation (Bfo) Algorithmmentioning

confidence: 99%

A Survey on Swarm Robotics for Area Coverage Problem

Muhsen,

Sadiq,

Raheem

2023

Algorithms

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“…There are many exploitation methods that have been widely studied and proposed based on swarm intelligence (SI) such as Particle Swarm Optimization [6][7][8], Ant Colony Optimization [9], Bean Optimization [10] and Bacteria Chemotaxis [11]. Other exploitation methods include pattern formation [12], infotaxis [13], behavior-based [14] and hybrid method [15].…”

Section: Introductionmentioning

confidence: 99%

Cooperative Source Detection Using an Optimized Distributed Levy Flight Algorithm

Ab. Majid,

Arshad,

Yahya

2023

Jurnal Teknologi

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Source signal detection plays important roles in many real-world target searching problems. Source detection is necessary before a full search process utilizing the detected signal can be performed where minimizing the detection time and maximizing the search space exploration or coverage are the main problems. In this paper, an optimized Levy Flight algorithm known as a Distributed Levy Flight (DLF) for swarm agents is proposed. The DLF algorithm is optimized by means of repulsive artificial potential force to disperse the agents in order to optimize the search space coverage and detection time. Additionally, to integrate cooperative behavior, an artificial attractive force is used to maintain communication among the agents. The results showed that the proposed DLF algorithm successfully improve detection time (113.1s) and area coverage (78.3%) compared to the existing algorithms: Brownian Walk (325.5s, 31.7%), Correlated Random Walk (356.2s, 35.1%), Levy Flight (201.3s, 56.6%), Levy Flight with Artificial Potential Fields (151.9s, 70.2%).

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“…Numerous articles have been written on the ingenuity of each of these mechanisms, some of which have even served as models for human innovation (Mohammadi et al 2017;Jiang et al 2021;Tachiyama et al 2022). One biologist observed that, " .…”

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confidence: 99%

On the Relationship between Design and Evolution

et al. 2023

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A longstanding question in science and religion is whether standard evolutionary models are compatible with the claim that the world was designed. In The Compatibility of Evolution and Design, theologian E. V. Rope Kojonen constructs a powerful argument that not only are evolution and design compatible, but that evolutionary processes (and biological data) strongly point to design. Yet Kojonen’s model faces several difficulties, each of which raise hurdles for his understanding of how evolution and design can be harmonized. First, his argument for design (and its compatibility with evolution) relies upon a particular view of nature in which fitness landscapes are “fine-tuned” to allow proteins to evolve from one form to another by mutation and selection. But biological data run contrary to this claim, which poses a problem for Kojonen’s design argument (and, as such, his attempt to harmonize design with evolution). Second, Kojonen appeals to the bacterial flagellum to strengthen his case for design, yet the type of design in the flagellum is incompatible with mainstream evolutionary theory, which (again) damages his reconciliation of design with evolution. Third, Kojonen regards convergent evolution as notable positive evidence in favor of his model (including his version of design), yet convergent evolution actually harms the justification of common ancestry, which Kojonen also accepts. This, too, mars his reconciliation of design and evolution. Finally, Kojonen’s model damages the epistemology that undergirds his own design argument as well as the design intuitions of everyday “theists on the street”, whom he seeks to defend. Thus, despite the remarkable depth, nuance, and erudition of Kojonen’s account, it does not offer a convincing reconciliation of ‘design’ and ‘evolution’.

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A Bacterial Chemotaxis-Inspired Coordination Strategy for Coverage and Aggregation of Swarm Robots

Cited by 6 publications

References 35 publications

A Survey on Swarm Robotics for Area Coverage Problem

A Survey on Swarm Robotics for Area Coverage Problem

Cooperative Source Detection Using an Optimized Distributed Levy Flight Algorithm

On the Relationship between Design and Evolution

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