[1]张飞,白伟,乔耀华,等.基于改进D*算法的无人机室内路径规划[J].智能系统学报,2019,14(04):662-669.[doi:10.11992/tis.201803031]
 ZHANG Fei,BAI Wei,QIAO Yaohua,et al.UAV indoor path planning based on improved D* algorithm[J].CAAI Transactions on Intelligent Systems,2019,14(04):662-669.[doi:10.11992/tis.201803031]
点击复制

基于改进D*算法的无人机室内路径规划(/HTML)
分享到:

《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第14卷
期数:
2019年04期
页码:
662-669
栏目:
出版日期:
2019-07-02

文章信息/Info

Title:
UAV indoor path planning based on improved D* algorithm
作者:
张飞1 白伟2 乔耀华3 邢伯阳2 周鹏程4
1. 山东鲁能智能技术有限公司, 山东 济南 250101;
2. 北京理工大学 自动化学院, 北京 100081;
3. 国网山东省电力公司, 山东 济南 250000;
4. 昆明北理工产业技术研究院有限公司, 云南 昆明 650000
Author(s):
ZHANG Fei1 BAI Wei2 QIAO Yaohua3 XING Boyang2 ZHOU Pengcheng4
1. Shandong Luneng Intelligence Technology Company Limited, Ji’nan 250101, China;
2. School of Automation, Beijing Institute of Technology, Beijing 100081, China;
3. State Grid Shandong Electric Power Company, Ji’nan 250000, China;
4. BIT Industrial Technology Research Institute, Kunming Company Limited, Kunming 650000, China
关键词:
无人机室内定位系统路径规划自主导航避障二维码数组ArUco改进D*算法
Keywords:
UAVindoor positioning systempath planningautonomous navigationobstacle avoidanceQR code arrayArUcoimproved D* algorithm
分类号:
TP29
DOI:
10.11992/tis.201803031
摘要:
针对多旋翼飞行器室内无GPS信号时的导航问题,本文采用二维码阵列构建室内定位系统,基于改进D*算法实现无人机室内路径规划,从而实现飞行器在室内的自主导航和避障。基于ArUco二维码设计了地面阵列为无人机提供了全局精确定位信息,使用改进D*算法保证了无人机在飞行过程中能自主进行路径规划和飞行。通过设计实验对改进D*算法进行了数值仿真验证,并在实际无人机的飞行中应用。实验结果证明:所提改进算法较传统D*算法能更好地保证无人机的飞行安全,同时基于二维码阵列的定位方式不但具有较高精度同时成本低易于实现。
Abstract:
Considering the navigation problem when there is no indoor GPS signal in a multi-rotorcraft, in this study, an indoor positioning system is constructed using a two-dimensional code array, and the indoor path planning of the unmanned aerial vehicle (UAV) is realized based on an improved D* algorithm, in order to realize autonomous navigation and obstacle avoidance of the aircraft indoors. Based on an ArUco two-dimensional code, the ground array was designed to provide accurate global positioning information for the UAV. The improved D* algorithm was used to ensure that the UAV can autonomously conduct path planning and flight during flight. Design experiments were carried out to simulate and verify the improved D* algorithm, which was further verified in an actual UAV flight application. The experimental results show that the improved algorithm can better guarantee the flight safety of the drone compared with the traditional D* algorithm. Moreover, the positioning method based on the two-dimensional code array is highly accurate, low-cost, and easy to implement.

参考文献/References:

[1] LIM H, PARK J, LEE D, et al. Build your own quadrotor:open-source projects on unmanned aerial vehicles[J]. IEEE robotics and automation magazine, 2012, 19(3):33-45.
[2] RASMUSSEN J, NIELSEN J, GARCIA-RUIZ F, et al. Potential uses of small unmanned aircraft systems (UAS) in weed research[J]. Weed research, 2013, 53(4):242-248.
[3] XIONG Jingjing, ZHENG Enhui. Position and attitude tracking control for a quadrotor UAV[J]. ISA transactions, 2014, 53(3):725-731.
[4] KOTTATH R, NARKHEDE P, KUMAR V, et al. Multiple model adaptive complementary filter for attitude estimation[J]. Aerospace science and technology, 2017, 69:574-581.
[5] 唐强, 张翔伦, 左玲. 无人机航迹规划算法的初步研究[J]. 航空计算技术, 2003, 33(1):125-128, 132 TANG Qiang, ZHANG Xianglun, ZUO Ling. Initial study on the path planning’s algorithms for unmanned aerial vehicles[J]. Aeronautical computer technique, 2003, 33(1):125-128, 132
[6] 王俊, 周树道, 朱国涛, 等. 无人机航迹规划常用算法[J]. 火力与指挥控制, 2012, 37(8):5-8 WANG Jun, ZHOU Shudao, ZHU Guotao, et al. Research of common route planning algorithms for unmanned air vehicle[J]. Fire control and command control, 2012, 37(8):5-8
[7] 白志君. 四旋翼无人机室内自主导航系统的研究与实现[D]. 厦门:厦门大学, 2014. BAI Zhijun. Study and realization on indoor autonomous navigation system for quad-copter[D]. Xiamen:Xiamen University, 2014.
[8] 何雨枫. 室内微小型无人机路径规划算法研究[D]. 南京:南京航空航天大学, 2014. HE Yufeng. Research on indoor MUAV path planning[D]. Nanjing:Nanjing University of Aeronautics and Astronautics, 2014.
[9] 黄媛媛. 基于数据融合的室内无人机导航避障研究[D]. 成都:成都理工大学, 2017. HUANG Yuanyuan. Research on navigation avoidance of indoor UAV based on data fusion[D]. Chengdu:Chengdu University of Technology, 2017.
[10] STENTZ A. The D* algorithm for real-time planning of optimal traverses[R]. Carnegie:Carnegie Mellon University, 1994.
[11] STENTZ A. The focussed D* algorithm for real-time replanning[C]//Proceedings of the 14th International Joint Conference on Artificial Intelligence. Montreal, Canada, 1995:1652-1659.
[12] HRABAR S. 3D path planning and stereo-based obstacle avoidance for rotorcraft UAVs[C]//Proceedings of 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems. Nice, France, 2008:807-814.
[13] 郑昌文. 飞行器航迹规划方法研究[D]. 武汉:华中科技大学, 2003. ZHENG Changwen. Research on route planning for air vehicles[D]. Wuhan:Huazhong University of Science and Technology, 2003.
[14] 符小卫, 高晓光. 一种无人机路径规划算法研究[J]. 系统仿真学报, 2004, 16(1):20-21, 34 FU Xiaowei, GAO Xiaoguang. Study on a kind of path planning algorithm for UAV[J]. Journal of system simulation, 2004, 16(1):20-21, 34
[15] GARRIDO-JURADO S, MUÑOZ-SALINAS,R, MADRID-CUEVAS F J, et al. Generation of fiducial marker dictionaries using mixed integer linear programming[J]. Pattern recognition, 2016,3(51):481-491.
[16] SUZUKI S, ABE K. Topological structural analysis of digitized binary images by border following[J]. Computer vision, graphics, and image processing, 1985, 30(1):32-46.
[17] DOUGLAS D H, PEUCKER T K. Algorithms for the reduction of the number of points required to represent a digitized line or its caricature[J]. Cartographica:the international journal for geographic information and geovisualization, 1973, 10(2):112-122.
[18] OTSU N. A threshold selection method from gray-level histograms[J]. IEEE transactions on systems, man, and cybernetics, 1979, 9(1):62-66.
[19] KRAJNÍK T, VONÁSEK V, FI?ER D, et al. AR-Drone as a platform for robotic research and education[J]//OBDR?ÁLEK D, GOTTSCHEBER A. Research and Education in Robotics-EUROBOT 2011. Berlin, Heidelberg:Springer, 2011:172-186.
[20] FERGUSON D, STENTZ A. Field D*:an interpolation-based path planner and replanner[M]//THRUN S, BROOKS R, DURRANT-WHYTE H. Robotics Research. Berlin, Heidelberg:Springer, 2007:239-253.
[21] 魏宁, 刘一松. 基于栅格模型的移动机器人全局路径规划研究[J]. 微计算机信息, 2008, 24(11):229-231 WEI Ning, LIU Yisong. Research on Grid-Base global path planning for mobile robot[J]. Control and automation, 2008, 24(11):229-231
[22] NEMRA A, AOUF N. Robust INS/GPS sensor fusion for UAV localization using SDRE nonlinear filtering[J]. IEEE sensors journal, 2010, 10(4):789-798.

相似文献/References:

[1]秦世引,潘宇雄,苏善伟.小型无人机编队飞行的控制律设计与仿真[J].智能系统学报,2009,4(03):218.
 QIN Shi-yin,PAN Yu-xiong,SU Shan-wei.Design and simulation of formation flight control laws for small unmanned aerial vehicles[J].CAAI Transactions on Intelligent Systems,2009,4(04):218.
[2]朱杰斌,秦世引.无人机编队飞行的分布式控制策略与控制器设计[J].智能系统学报,2010,5(05):392.[doi:10.3969/j.issn.1673-4785.2010.05.003]
 ZHU Jie-bin,QIN Shi-yin.Distributed control strategy and controller design for UAV formation flight[J].CAAI Transactions on Intelligent Systems,2010,5(04):392.[doi:10.3969/j.issn.1673-4785.2010.05.003]
[3]刘敏,邹杰,冯星,等.人工蜂群算法的无人机航路规划与平滑[J].智能系统学报,2011,6(04):344.
 LIU Min,ZOU Jie,FENG Xing,et al.Smooth trajectory planning of an unmanned aerial vehicleusing an artificial bee colony algorithm[J].CAAI Transactions on Intelligent Systems,2011,6(04):344.
[4]胡文超,孙新柱,陈孟元.音频感知哈希闭环检测的无人机仿生声呐SLAM算法研究[J].智能系统学报,2019,14(02):338.[doi:10.11992/tis.201708018]
 HU Wenchao,SUN Xinzhu,CHEN Mengyuan.Research on BATSLAM algorithm for UAV based on audio perceptual hash closed-loop detection[J].CAAI Transactions on Intelligent Systems,2019,14(04):338.[doi:10.11992/tis.201708018]
[5]徐魏超,王冠凌,陈孟元.无人机协助下基于SR-CKF的无线传感器网络节点定位研究[J].智能系统学报,2019,14(03):575.[doi:10.11992/tis.201709019]
 XU Weichao,WANG Guanling,CHEN Mengyuan.Node localization of wireless sensor networks based on SR-CKF assisted by unmanned aerial vehicles[J].CAAI Transactions on Intelligent Systems,2019,14(04):575.[doi:10.11992/tis.201709019]

备注/Memo

备注/Memo:
收稿日期:2018-03-20。
作者简介:张飞,男,1988年生,工程师,主要研究方向为无人机检测、无人机巡检技术;白伟,男,1992年生,硕士研究生,主要研究方向为无人机控制;乔耀华,男,1982年生,副高级工程师,国网优秀专家人才,主要研究方向为输电运维检修、输电线路运行、检修管理。发表学术论文专著6项。
通讯作者:张飞.E-mail:821661887@qq.com
更新日期/Last Update: 2019-08-25