Constructing a cohesive pattern for collective navigation based on a swarm of robotics

• Published in: PeerJ. Computer science Vol. 7; p. e626
• Main Authors: Soliman, Yehia A, Abdulkader, Sarah N, Mohamed, Taha M
• Format: Journal Article
• Language: English
• Published: San Diego PeerJ. Ltd 27.07.2021; PeerJ, Inc; PeerJ Inc
• Subjects: Adaptive and Self-Organizing Systems; Agents and Multi-Agent Systems; Agglomeration; Aggregation algorithm; Algorithms; Analysis; Artificial Intelligence; Collective navigation; Communication; Evolution; Literature reviews; Mobile robots; Navigation; Pheromones; Robotics; Robots; Swarm robotics; Task complexity; Variance analysis
• ISSN: 2376-5992; 2376-5992
• DOI: 10.7717/peerj-cs.626

Swarm robotics carries out complex tasks beyond the power of simple individual robots. Limited capabilities of sensing and communication by simple mobile robots have been essential inspirations for aggregation tasks. Aggregation is crucial behavior when performing complex tasks in swarm robotics systems. Many difficulties are facing the aggregation algorithm. These difficulties are as such: this algorithm has to work under the restrictions of no information about positions, no central control, and only local information interaction among robots. This paper proposed a new aggregation algorithm. This algorithm combined with the wave algorithm to achieve collective navigation and the recruitment strategy. In this work, the aggregation algorithm consists of two main phases: the searching phase, and the surrounding phase. The execution time of the proposed algorithm was analyzed. The experimental results showed that the aggregation time in the proposed algorithm was significantly reduced by 41% compared to other algorithms in the literature. Moreover, we analyzed our results using a one-way analysis of variance. Also, our results showed that the increasing swarm size significantly improved the performance of the group.