[1]曾庆山,冯珊珊.一种基于改进适应度的多机器人协作策略[J].郑州大学学报(工学版),2018,39(02):6-10.[doi:10.13705/j.issn.1671-6833.2018.02.003]
Zeng Qingshan,Feng Shanshan.A Multi-robot Cooperative Strategy Based on Improved Fitness Function6[J].Journal of Zhengzhou University (Engineering Science),2018,39(02):6-10.[doi:10.13705/j.issn.1671-6833.2018.02.003]
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一种基于改进适应度的多机器人协作策略(
)
《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]
- 卷:
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39
- 期数:
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2018年02期
- 页码:
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6-10
- 栏目:
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- 出版日期:
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2018-03-30
文章信息/Info
- Title:
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A Multi-robot Cooperative Strategy Based on Improved Fitness Function6
- 作者:
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曾庆山; 冯珊珊
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郑州大学电气工程学院,河南郑州,450001
- Author(s):
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Zeng Qingshan; Feng Shanshan
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School of Electrical Engineering, Zhengzhou University, Zhengzhou, Henan, 450001
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- 关键词:
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- Keywords:
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- DOI:
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10.13705/j.issn.1671-6833.2018.02.003
- 文献标志码:
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A
- 摘要:
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通过对基于适应度的协作策略及其改进方法的研究发现，针对机器人在两个任务的适应度相同机无法选择出最匹配的任务，提出通过加入与机器人起止位置有关的距离适应度函数，使得机器人可以选择出最优匹配的任务；同时，针对外部能力适应度，采用更符合实际的高斯分布模型来计算适应度。仿真结果表明，改进后的算法不仅实现了最优匹配，而且算法更高效，更节省能量。
- Abstract:
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This study focused on the fitness-based cooperative strategy and its improvement method. It was found that the problem of the most matching task could not be decided when the robot had the same fitness tasks. By adding the distance fitness function related to the robot’s starting and ending pisotion, the robot could choose the best matching task. At the same time, more realistic Gaussian distribution model is used to calculate the fitness of the external ability. The simulation results showed that the improved algorithm could not only achieve the optimal matching , but also be more efficient and energy saving than before.
更新日期/Last Update:
2018-04-01