Honey Bee Swarm Inspired Cooperative Foraging Systems in Dynamic Environments

Jong-Hyun LEE; Jinung AN; Chang Wook AHN

doi:10.1587/transfun.E99.A.1171

Honey Bee Swarm Inspired Cooperative Foraging Systems in Dynamic Environments

Jong-Hyun LEE, Jinung AN, Chang Wook AHN

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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%.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E99-A No.6 pp.1171-1178

Publication Date: 2016/06/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E99.A.1171

Type of Manuscript: PAPER

Category: Systems and Control

Authors

Jong-Hyun LEE
  Sungkyunkwan University (SKKU)
Jinung AN
  Daegu Gyeongbuk Institute of Science & Technology (DGIST)
Chang Wook AHN
  Sungkyunkwan University (SKKU)

Keyword

honey bee swarm, swarm robotics, cooperative algorithm, foraging task

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Jong-Hyun LEE, Jinung AN, Chang Wook AHN, "Honey Bee Swarm Inspired Cooperative Foraging Systems in Dynamic Environments" in IEICE TRANSACTIONS on Fundamentals, vol. E99-A, no. 6, pp. 1171-1178, June 2016, doi: 10.1587/transfun.E99.A.1171.
Abstract: 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%.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E99.A.1171/_p

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@ARTICLE{e99-a_6_1171,
author={Jong-Hyun LEE, Jinung AN, Chang Wook AHN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Honey Bee Swarm Inspired Cooperative Foraging Systems in Dynamic Environments},
year={2016},
volume={E99-A},
number={6},
pages={1171-1178},
abstract={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%.},
keywords={},
doi={10.1587/transfun.E99.A.1171},
ISSN={1745-1337},
month={June},}

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TY - JOUR
TI - Honey Bee Swarm Inspired Cooperative Foraging Systems in Dynamic Environments
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1171
EP - 1178
AU - Jong-Hyun LEE
AU - Jinung AN
AU - Chang Wook AHN
PY - 2016
DO - 10.1587/transfun.E99.A.1171
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E99-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 2016
AB - 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%.
ER -