无人机多机协作探索煤矿灾变环境算法

doi:10.11772/j.issn.1001-9081.2017.08.2401

计算机应用 ›› 2017, Vol. 37 ›› Issue (8): 2401-2404.DOI: 10.11772/j.issn.1001-9081.2017.08.2401

• 应用前沿、交叉与综合 • 上一篇下一篇

无人机多机协作探索煤矿灾变环境算法

刘栋, 童敏明, 路红蕊

中国矿业大学信息与控制工程学院, 江苏徐州 221008

收稿日期:2017-02-20 修回日期:2017-04-05 出版日期:2017-08-10 发布日期:2017-08-12
作者简介:刘栋(1991-),女,湖南岳阳人,硕士研究生,主要研究方向:人工智能、信号处理;童敏明(1956-),男,浙江龙游人,教授,博士,主要研究方向:人工智能、数据分析与处理、图像处理;路红蕊(1991-),女,河南濮阳人,硕士研究生,主要研究方向:人工智能、图像处理。
基金资助:
"十三五"国家重点研发计划项目（2016YFC0801808）。

Algorithm for exploring coal mine disaster environment by multi-UAV cooperation

LIU Dong, TONG Minming, LU Hongrui

School of Information and Control Engineering, China University of Mining and Technology, Xuzhou Jiangsu 221008, China

Received:2017-02-20 Revised:2017-04-05 Online:2017-08-10 Published:2017-08-12
Supported by:
This work is partially supported by" "the 13th Five-Year Plan" "National Key Research and Development Program of China (2016YFC0801808)

摘要/Abstract

摘要： 针对目前煤矿灾变环境下救援机器人探索效率低的问题，提出了一种使用无人机多机协同探索煤矿灾变环境的改进型边界探索算法。该算法在效用值边界探索算法的基础上增加了对无人机导航角度因素的考虑，同时引入分散度函数作为评判机制来构建目标函数，并使用蚁群算法对该目标函数进行求解。最后利用Matlab软件在栅格化地图上进行了仿真实验。实验结果表明，和效用值边界探索算法相比，改进型边界探索算法减少了探测过程中的重复覆盖和拥挤现象，缩短了探测时间，降低了约30%的能量消耗，提高了无人机多机系统的整体探索效率。

关键词: 无人机多机, 边界探索, 分散度函数, 环境侦测, 探索效率

Abstract: Focusing on the low efficiency of the rescue robot in the coal mine disaster environment, a new improved boundary exploration algorithm based on multiple Unmanned Aerial Vehicles (multi-UAV) was proposed. Based on the utility value boundary exploration algorithm, the flight angle parameter of UAV was considered, and the distribution function was introduced as a judgment mechanism to construct the objective function. Finally, the ant colony algorithm was used to solve the objective function. Simulation experiments were carried out on a rasterized map with Matlab software. The simulation results show that the improved boundary exploration algorithm can reduce the phenomenon of repeated coverage and crowding, shorten the detection time, meanwhile the energy required by UAV is reduced by about 30%, thus improving the overall exploration efficiency of multi-UAV system.

Key words: multiple Unmanned Aerial Vehicle (multi-UAV), boundary exploration, distribution function, environment detection, exploration efficiency

中图分类号:

TP242.6

刘栋, 童敏明, 路红蕊. 无人机多机协作探索煤矿灾变环境算法[J]. 计算机应用, 2017, 37(8): 2401-2404.

LIU Dong, TONG Minming, LU Hongrui. Algorithm for exploring coal mine disaster environment by multi-UAV cooperation[J]. Journal of Computer Applications, 2017, 37(8): 2401-2404.

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无人机多机协作探索煤矿灾变环境算法

Algorithm for exploring coal mine disaster environment by multi-UAV cooperation

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