[1]范英盛,齐小刚,刘立芳.协同定位中的坐标配准策略研究[J].智能系统学报,2021,16(3):459-465.[doi:10.11992/tis.202012015]
FAN Yingsheng,QI Xiaogang,LIU Lifang.Coordinate registration strategy in cooperative localization[J].CAAI Transactions on Intelligent Systems,2021,16(3):459-465.[doi:10.11992/tis.202012015]
点击复制
FAN Yingsheng,QI Xiaogang,LIU Lifang.Coordinate registration strategy in cooperative localization[J].CAAI Transactions on Intelligent Systems,2021,16(3):459-465.[doi:10.11992/tis.202012015]
协同定位中的坐标配准策略研究
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
16
期数:
2021年第3期
页码:
459-465
栏目:
学术论文—智能系统
出版日期:
2021-05-05
- Title:
- Coordinate registration strategy in cooperative localization
- Keywords:
- cooperative localization; positioning algorithm; coordinate registration; least square algorithm; Procrustes analysis; anchor node; average connectivity; range error
- 分类号:
- TP391
- 摘要:
- 坐标配准是协同定位的重要组成部分，一个合理的坐标配准体系可以体现协同定位算法的性能，否则可能会放大定位算法的误差。本文详细比较了基于最小二乘 (least square, LS)与基于普氏分析(Procrustes analysis, PA)的配准方法的设计思想、适用条件，并给出了基于普氏分析的坐标配准算法的详细步骤。利用协同定位算法(经典MDS和Levenberg–Marquardt算法)得到的实验数据，详细分析了锚节点数量、测距误差、网络节点平均连通度对配准精度的影响。实验表明，在2D和3D环境中，基于普氏分析的配准算法，其配准精度和稳定性都优于最小二乘法，配准误差降低约为20%。
- Abstract:
- Coordinate registration is an integral part of cooperative localization. A good coordinate registration system can improve the performance of collaborative location algorithms; otherwise, it may increase their errors. This paper carefully compares the design ideas and applicable conditions of coordinate registration methods based on the least square (LS) method and Procrustes analysis (PA). Detailed steps of the coordinate registration algorithm based on PA are provided. Using the experimental data obtained from the cooperative localization algorithms (classical MDS and Levenberg-Marquardt algorithm), the effects of the number of anchor nodes, range error, and average connectivity of the network nodes on the registration accuracy were analyzed in detail. The experimental results showed that in 2D and 3D environments, the PA-based algorithm has better registration accuracy and stability than the LS-based algorithm, with registration error reduced by approximately 20%.
- 参考文献/References:
-
[1] WANASINGHE T R, MANN G K I, GOSINE R G. Distributed leader-assistive localization method for a heterogeneous multirobotic system[J]. IEEE transactions on automation science and engineering, 2015, 12(3):795-809.
[2] YAN Yuan, MOSTOFI Y. Robotic router formation in realistic communication environments[J]. IEEE transactions on robotics, 2012, 28(4):810-827.
[3] SUN Qian, TIAN Yu, DIAO Ming. Cooperative localization algorithm based on Hybrid topology architecture for multiple mobile robot system[J]. IEEE internet of things journal, 2018, 5(6):4753-4763.
[4] WANG Chunxiang, HUANG Hairu, JI Yang, et al. Vehicle localization at an intersection using a traffic light map[J]. IEEE transactions on intelligent transportation systems, 2019, 20(4):1432-1441.
[5] DENTLER J, KANNAN S, BEZZAOUCHA S, et al. Model predictive cooperative localization control of multiple UAVs using potential function sensor constraints:a workflow to create sensor constraint based potential functions for the control of cooperative localization scenarios with mobile robots[J]. Autonomous robots, 2019, 43(1):153-178.
[6] WANG Xianpeng, YANG L T, MENG Dandan, et al. Multi-UAV cooperative localization for marine targets based on weighted subspace fitting in SAGIN environment[EB/OL]. (2021?3?17)[2021?4?30]https://ieeexplore.ieee.org/document/9380358.
[7] 朱健楠, 虞梦苓, 杨益新. 无人水面艇感知技术发展综述[J]. 哈尔滨工程大学学报, 2020, 41(10):1486-1492
ZHU Jiannan, YU Mengling, YANG Yixin. Overview of development of unmanned-surface-vehicle sensing technology[J]. Journal of Harbin Engineering University, 2020, 41(10):1486-1492
[8] SHIT R C. Precise localization for achieving next- generation autonomous navigation:State-of-the-Art, taxonomy and future prospects[J]. Computer communications, 2020, 160:351-374.
[9] ZHU Yanbo, LIU Yuan, WANG Zhipeng. Evaluation of GBAS flight trials based on BDS and GPS[J]. IET radar, sonar & navigation, 2020, 14(2):233-241.
[10] 席志红, 占梦奇. 基于位置范围限定的WiFi-KNN室内定位算法[J]. 应用科技, 2020, 47(4):66-70
XI Zhihong, ZHAN Mengqi. WiFi-KNN indoor positioning algorithm based on location range limitation[J]. Applied science and technology, 2020, 47(4):66-70
[11] JIN Bonan, XU Xiaosu, ZHU Yongyun, et al. Single-source aided semi-autonomous passive location for correcting the position of an underwater vehicle[J]. IEEE sensors journal, 2019, 19(9):3267-3275.
[12] WYMEERSCH H, LIEN J, WIN M Z. Cooperative localization in wireless networks[J]. Proceedings of the IEEE, 2009, 97(2):427-450.
[13] FAN Yingsheng, QI Xiaogang, LIU Lifang. Fault-tolerant cooperative localization of 3D mobile networks via two-layer filter multidimensional scaling[J]. IEEE sensors journal, 2021, 21(6):8354-8366.
[14] SHIT R C, SHARMA S, PUTHAL D, et al. Ubiquitous Localization (UbiLoc):a survey and taxonomy on device free localization for smart world[J]. IEEE communications surveys & tutorials, 2019, 21(4):3532-3564.
[15] PIOVESAN N, ERSEGHE T. Cooperative localization in WSNs:a hybrid convex/nonconvex solution[J]. IEEE transactions on signal and information processing over networks, 2018, 4(1):162-172.
[16] SHANG Y, RUMI W, ZHANG Y, et al. Localization from connectivity in sensor networks[J]. IEEE transactions on parallel and distributed systems, 2004, 15(11):961-974.
[17] COSTA J A, PATWARI N, HERO A O. Distributed weighted multi-dimensional scaling for node localization in sensor networks[J]. ACM transactions on sensor networks, 2006, 2(1):39-64.
[18] NOCEDAL J, WRIGHT S J. Numerical optimization[M]. 2nd ed. Berlin:Springer, 2006:250-274.
[19] FAN Yingsheng, QI Xiaogang, LI Bo, et al. Fast clustering-based multidimensional scaling for mobile networks localisation[J]. IET communications, 2020, 14(1):135-143.
[20] 马兰芝, 管亮, 冯新泸, 等. 基于普鲁克分析的润滑油红外光谱指纹区相似度评价方法[J]. 石油学报(石油加工), 2013, 29(5):891-898
MA Lanzhi, GUAN Liang, FENG Xinlu, et al. The method of similarity determination for lubricating Oil infrared fingerprint by Procrustes Analysis[J]. Acta petrolei sinica (petroleum processing section), 2013, 29(5):891-898
[21] 陈智强, 王作伟, 方龙伟, 等. 基于机器学习和几何变换的实时2D/3D脊椎配准[J]. 自动化学报, 2018, 44(7):1183-1194
CHEN Zhiqiang, WANG Zuowei, FANG Longwei, et al. Real-time 2D/3D registration of vertebra via machine learning and geometric transformation[J]. Acta automatica sinica, 2018, 44(7):1183-1194
[22] 成翔昊, 达飞鹏, 汪亮. 基于融合约束局部模型的三维人脸特征点定位[J]. 浙江大学学报(工学版), 2019, 53(4):770-776
CHENG Xianghao, DA Feipeng, WANG Liang. Feature fusion based constrained local model for three- dimensional facial landmark localization[J]. Journal of Zhejiang University (engineering science), 2019, 53(4):770-776
[23] 熊玉雪, 杨慧芳, 赵一姣, 等. 两种评价面部三维表面数据不对称度方法的比较[J]. 北京大学学报(医学版), 2015, 47(2):340-343
XIONG Yuxue, YANG Huifang, ZHAO Yijiao, et al. Comparison of two kinds of methods evaluating the degree of facial asymmetry by three-dimensional data[J]. Journal of Peking University (health sciences), 2015, 47(2):340-343
[24] BAI Xuefeng, CAO Hailong, CHEN Kehai, et al. A bilingual adversarial autoencoder for unsupervised bilingual lexicon induction[J]. IEEE/ACM transactions on audio, speech, and language processing, 2019, 27(10):1639-1648.
[25] GOWER J C, DIJKSTERHUIS G B. Procrustes problems[M]. Oxford:Oxford University Press, 2004:29-48.
[26] MOHAMMADREZA D. Minimal driver nodes for structural controllability of large-scale dynamical systems:node classification[J]. IEEE systems journal, 2020, 14(3):4209-4216.
- 相似文献/References:
-
[1]程磊,周明达,吴怀宇,等.无线传感器环境下粒子群优化的多机器人协同定位研究[J].智能系统学报,2015,10(1):138.[doi:10.3969/j.issn.1673-4785.201310067]
CHENG Lei,ZHOU Mingda,WU Huaiyu,et al.Cooperative multi-robot localization based on particle swarm optimization in the environment of wireless sensor[J].CAAI Transactions on Intelligent Systems,2015,10():138.[doi:10.3969/j.issn.1673-4785.201310067]
[2]田仲富,王述洋,黄英来.基于无线传感器的嵌入式森林防火智能监测系统[J].智能系统学报,2014,9(6):763.[doi:10.3969/j.issn.1673-4785.201406036]
TIAN Zhongfu,WANG Shuyang,HUANG Yinglai.Research on embedded forest fire intelligent monitoring system based on wireless sensors[J].CAAI Transactions on Intelligent Systems,2014,9():763.[doi:10.3969/j.issn.1673-4785.201406036]
备注/Memo
收稿日期:2020-12-07。
基金项目:国家自然科学基金项目(61877067)；数据链技术重点实验室基金项目(CLDL-20182115)；近地面探测与感知技术重点实验室基金项目(TCGZ2019A002)；基础研究项目(61424140502)
作者简介:范英盛，讲师，博士研究生，主要研究方向为动态集群网络的协同定位;齐小刚，教授，博士生导师，博士，主要研究方向为复杂系统建模与仿真、网络算法设计与应用。主持国家自然科学基金项目、十三五装备预研项目等国家和省部级项目20余项。获授权专利19项，软件著作权4项。发表学术论文100余篇;刘立芳，教授，博士，主要研究方向为数据处理与智能计算。主持国家自然科学基金项目、陕西省自然科学基金项目等国家和省部级项目5项。发表学术论文40余篇
通讯作者:齐小刚.E-mail:xgqi@xidian.edu.cn
更新日期/Last Update:
2021-06-25