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Honey Bee Swarm Inspired Cooperative Foraging Systems in Dynamic Environments

Honey Bee Swarm Inspired Cooperative Foraging Systems in Dynamic Environments
Lee, JH[Lee, Jong-Hyun]An, J[An, Jinung]Ahn, CW[Ahn, Chang Wook]
DGIST Authors
An, J[An, Jinung]
Issued Date
Article Type
Collector EfficiencyConsumption of EnergyConventional MethodsCooperative AlgorithmCost ReductionCostsData Communication EquipmentEfficiency ComparisonsEnergy ConservationEnergy EfficiencyFault ToleranceFood ProductsForaging Swarm RobotsForaging TaskHoney Bee SwarmHoney Bee SwarmsOperating CostsRobotsSwarm Robotics
Operating swarm robots has the virtues of improved performance, fault tolerance, distributed sensing, and so on. The problem is, high overall system costs are the main barrier in managing a system of foraging swarm robots. Moreover, its control algorithm should be scalable and reliable as the foraging (search) spaces become wider. This paper analyzes a nature-inspired cooperative method to reduce the operating costs of the foraging swarm robots through simulation experiments. The aim of this research is to improve efficiency of mechanisms for reducing the cost by developing a new algorithm for the synergistic cooperation of the group. In this paper, we set the evaluation index of energy efficiency considering that the mission success rate as well as energy saving is important. The value is calculated as the number of successful operations against the total consumption of energy in order to also guarantee optimized for the work processing power than the one simple goal of energy savings. The method employs a behavioral model of a honey bee swarm to improve the energy efficiency in collecting crops or minerals. Experiments demonstrate the effectiveness of the approach. The experiment is set a number of strategies to combine the techniques to the proposed and conventional methods. Considering variables such as the area of search space and the size of a swarm, the efficiency comparison test is performed. As the result, the proposed method showed the enhanced energy efficiency of the average 76.9% as compared to the conventional simple model that means reduction of the recharging cost more than 40%. Copyright © 2016 The Institute of Electronics, Information and Communication Engineers.
Related Researcher
  • 안진웅 An, Jinung 지능형로봇연구부
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Appears in Collections:
ETC 1. Journal Articles
Division of Intelligent Robotics Brain Robot Augmented InteractioN(BRAIN) Laboratory 1. Journal Articles


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