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基于模糊层次分析法和合作博弈理论的多移动机器人导航算法。

A Fuzzy Analytic Hierarchy Process and Cooperative Game Theory Combined Multiple Mobile Robot Navigation Algorithm.

机构信息

Daegu Research Center for Medical Devices and Rehabilitation, Korea Institute of Machinery and Materials, Daegu 42994, Korea.

Department of Mechanical and Automotive Engineering, Jeonju University, Jeonju 55069, Korea.

出版信息

Sensors (Basel). 2020 May 16;20(10):2827. doi: 10.3390/s20102827.

DOI:10.3390/s20102827
PMID:32429339
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7288072/
Abstract

This study presents a multi-robot navigation strategy based on a multi-objective decision-making algorithm, the Fuzzy Analytic Hierarchy Process (FAHP). FAHP analytically selects an optimal position as a sub-goal among points on the sensing boundary of a mobile robot considering the following three objectives: the travel distance to the target, collision safety with obstacles, and the rotation of the robot to face the target. Alternative solutions are evaluated by quantifying the relative importance of the objectives. As the FAHP algorithm is insufficient for multi-robot navigation, cooperative game theory is added to improve it. The performance of the proposed multi-robot navigation algorithm is tested with up to 12 mobile robots in several simulation conditions, altering factors such as the number of operating robots and the warehouse layout.

摘要

本研究提出了一种基于多目标决策算法——模糊层次分析法（FAHP）的多机器人导航策略。FAHP 通过分析在移动机器人的感测边界上的点，选择一个最佳位置作为子目标，该最佳位置考虑了以下三个目标：到目标的行进距离、与障碍物的碰撞安全性以及机器人转向以面对目标的旋转角度。通过量化目标的相对重要性来评估替代解决方案。由于 FAHP 算法对于多机器人导航来说还不够完善，因此添加了合作博弈论来对其进行改进。在所提出的多机器人导航算法的性能测试中，使用了多达 12 个移动机器人在几种模拟条件下，改变了操作机器人的数量和仓库布局等因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/ebb5d2b964c2/sensors-20-02827-g014.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/210840017e29/sensors-20-02827-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/c88c02836957/sensors-20-02827-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/9f0b7bb8fd92/sensors-20-02827-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/a3534ccb24d5/sensors-20-02827-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/ebb5d2b964c2/sensors-20-02827-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/b45c72cde14e/sensors-20-02827-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/4e071b3dc745/sensors-20-02827-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/1e577f7b3612/sensors-20-02827-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/35e99fc022df/sensors-20-02827-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/b7bdf0178f3c/sensors-20-02827-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/210840017e29/sensors-20-02827-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/c88c02836957/sensors-20-02827-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/9f0b7bb8fd92/sensors-20-02827-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/a3534ccb24d5/sensors-20-02827-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/c5145c1f7fb4/sensors-20-02827-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/d01298e66ccb/sensors-20-02827-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f4/7288072/ebb5d2b964c2/sensors-20-02827-g014.jpg

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引用本文的文献

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