Bflier's: A Novel Butterfly Inspired Multi-robotic Model in Search of Signal Sources
Chakravarthi J, Vinod Babu P, Pavan B, Ashok U, Marek Kolencik, Martin, \v{S}ebesta, Ramakanth Illa

TL;DR
This paper introduces a butterfly-inspired multi-robotic model utilizing the Butterfly Mating Optimization algorithm for detecting static and dynamic signal sources, demonstrating its effectiveness in real-time experiments.
Contribution
The work presents a novel multi-robotic system modeled after butterfly behavior and applies BMO for multi-signal source detection in dynamic environments.
Findings
BMO effectively detects multiple static and moving signal sources.
Swarm behavior adapts to different source movements with varying initial conditions.
Real-time experiments validate the applicability of the model in dynamic scenarios.
Abstract
The diversified ecology in nature had various forms of swarm behaviors in many species. The butterfly species is one of the prominent and a bit insightful in their random flights and converting that into an artificial metaphor would lead to enormous possibilities. This paper considers one such metaphor known as Butterfly Mating Optimization (BMO). In BMO, the Bfly follows the patrolling mating phenomena and simultaneously captures all the local optima of multimodal functions. To imitate this algorithm, a mobile robot (Bflybot) was designed to meet the features of the Bfly in the BMO algorithm. Also, the multi-Bflybot swarm is designed to act like butterflies in nature and follow the algorithm's rules. The real-time experiments were performed on the BMO algorithm in the multi-robotic arena and considered the signal source as the light source. The experimental results show that the BMO…
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Taxonomy
TopicsMetaheuristic Optimization Algorithms Research · Underwater Vehicles and Communication Systems · UAV Applications and Optimization
