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A Multiple Pheromone Communication System for Swarm Intelligence

delete2021-01-01
delete6
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OA
AI
T
Tian Liu
孙学龙 cover
孙学龙 (Xuelong Sun)
C
Cheng Hu
傅沁冰 cover
傅沁冰 (Qinbing Fu)
S
Shigang Yue *
DOI:10.1109/ACCESS.2021.3124386delete
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Abstract

Abstract

En 中文
Pheromones are chemical substances essential for communication among social insects. In the application of swarm intelligence to real micro mobile robots, the deployment of a single virtual pheromone has emerged recently as a powerful real-time method for indirect communication. However, these studies usually exploit only one kind of pheromones in their task, neglecting the crucial fact that in the world of real insects, multiple pheromones play important roles in shaping stigmergic behaviors such as foraging or nest building. To explore the multiple pheromones mechanism which enable robots to solve complex collective tasks efficiently, we introduce an artificial multiple pheromone system (ColCOS Phi) to support swarm intelligence research by enabling multiple robots to deploy and react to multiple pheromones simultaneously. The proposed system ColCOS Phi uses optical signals to emulate different evaporating chemical substances i.e. pheromones. These emulated pheromones are represented by trails displayed on a wide LCD display screen positioned horizontally, on which multiple miniature robots can move freely. The color sensors beneath the robots can detect and identify lingering pheromones on the screen. Meanwhile, the release of any pheromone from each robot is enabled by monitoring its positional information over time with an overhead camera. No other communication methods apart from virtual pheromones are employed in this system. Two case studies have been carried out which have verified the feasibility and effectiveness of the proposed system in achieving complex swarm tasks as empowered by multiple pheromones. This novel platform is a timely and powerful tool for research into swarm intelligence.
Keywords:
Robots
Robot sensing systems
Task analysis
Sensors
Optical sensors
Particle swarm optimization
Insects
Virtual pheromones
multiple pheromones
bio-inspired
swarm intelligence
micro mobile robots
swarm insects

Journal

IEEE Access cover
IEEE Access
IF:
3.6
Papers:
9.8W
Citations:
29.4W

Organization

U
University of Lincoln
Scholars:
2.6K
Papers: 2.6K
Citations: 3.9K