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移动机器人导航定位技术
作   译   者:赵红梅 等 出 版 日 期:2025-05-01
出   版   社:电子工业出版社 维   护   人:刘小琳 
书   代   号:TP499260 I S B N:9787121499265

图书简介:

本书针对移动机器人中涉及的主要无线导航定位技术的最新研究成果进行了论述,涵盖了近年来作者团队在无线导航定位技术路径规划、定位算法及系统构架等方面取得的成果。全书共6 章,第1 章从移动机器人的概念入手,回顾了其发展历程和关键技术,深入探讨了导航定位的概念、分类及其发展趋势;第2 章详细介绍了移动机器人涉及的各种导航定位技术;第3 章详细介绍了UWB 定位技术的特点、应用及系统构成,深入介绍了UWB 脉冲的产生、调制技术及其接收机设计、UWB 室内定位算法的实现等;第4 章从惯性导航技术的基本概念和发展状况出发,介绍了惯性导航的基础理论、捷联惯性导航方法及其在各领域的应用,并对惯性导航定位技术的进展及未来发展趋势进行了介绍;第5 章介绍了SLAM 系统的各种算法、发展中存在的问题与对策,并为读者展示了SLAM 技术的最新研究方向和应用前景;第6 章详细论述了多源信息融合算法及其在组合导航中的应用。
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    内容简介

    本书针对移动机器人中涉及的主要无线导航定位技术的最新研究成果进行了论述,涵盖了近年来作者团队在无线导航定位技术路径规划、定位算法及系统构架等方面取得的成果。全书共6 章,第1 章从移动机器人的概念入手,回顾了其发展历程和关键技术,深入探讨了导航定位的概念、分类及其发展趋势;第2 章详细介绍了移动机器人涉及的各种导航定位技术;第3 章详细介绍了UWB 定位技术的特点、应用及系统构成,深入介绍了UWB 脉冲的产生、调制技术及其接收机设计、UWB 室内定位算法的实现等;第4 章从惯性导航技术的基本概念和发展状况出发,介绍了惯性导航的基础理论、捷联惯性导航方法及其在各领域的应用,并对惯性导航定位技术的进展及未来发展趋势进行了介绍;第5 章介绍了SLAM 系统的各种算法、发展中存在的问题与对策,并为读者展示了SLAM 技术的最新研究方向和应用前景;第6 章详细论述了多源信息融合算法及其在组合导航中的应用。

    图书详情

    ISBN:9787121499265
    开 本:16(170*240)
    页 数:388
    字 数:590

    本书目录

    第1 章 绪论········································································································1
    1.1 移动机器人的概念···························································································1
    1.2 移动机器人的发展···························································································2
    1.3 移动机器人的关键技术·····················································································3
    1.4 导航定位的概念和分类·····················································································4
    1.5 导航定位技术的发展趋势··················································································5
    参考文献·············································································································6
    第2 章 常用的导航定位技术············································································7
    2.1 卫星导航定位技术··························································································7
    2.1.1 卫星导航定位系统的发展·······································································7
    2.1.2 国内外卫星导航定位系统介绍··································································8
    2.1.3 卫星导航定位系统的组成·····································································.11
    2.1.4 卫星导航定位技术简介········································································.16
    2.2 SLAM 导航定位技术····················································································.18
    2.2.1 SLAM 常用传感器概述········································································.19
    2.2.2 VSLAM····························································································.19
    2.2.3 LidarSLAM························································································.20
    2.3 其他导航定位技术·······················································································.21
    2.3.1 Wi-Fi 定位技术···················································································.21
    2.3.2 蓝牙定位技术····················································································.24
    2.3.3 ZigBee 定位技术·················································································.27
    2.3.4 RFID 定位技术···················································································.29
    2.3.5 地磁定位技术····················································································.32
    2.3.6 智能天线定位技术··············································································.35
    2.3.7 超声波定位技术·················································································.38
    2.3.8 红外线定位技术·················································································.40
    参考文献··········································································································.41
    第3 章 UWB 室内定位技术·········································································.46
    3.1 UWB 技术概述···························································································.46
    3.1.1 UWB 技术定义···················································································.46
    3.1.2 UWB 技术特点···················································································.47
    3.1.3 UWB 技术的应用················································································.47
    3.1.4 UWB 室内定位原理及系统构成······························································.49
    3.2 UWB 脉冲的产生和调制···············································································.51
    3.2.1 UWB 信号的实现方法··········································································.51
    3.2.2 常用的脉冲模板·················································································.54
    3.2.3 基于数字逻辑电路的窄脉冲设计····························································.72
    3.2.4 基于双非门结构的窄脉冲设计·······························································.80
    3.2.5 UWB 脉冲信号的调制··········································································.84
    3.3 UWB 接收机设计························································································.95
    3.3.1 接收机同步原理·················································································.96
    3.3.2 UWB 接收机原理及结构·······································································.98
    3.3.3 方案设计··························································································102
    3.4 UWB 室内定位算法研究···············································································129
    3.4.1 研究现状··························································································129
    3.4.2 常用定位算法简介··············································································131
    3.4.3 UWB 室内定位算法的数学模型······························································135
    3.4.4 UWB 厘米级室内定位算法设计······························································141
    3.4.5 基于实际UWB 信道模型的定位算法设计·················································150
    3.4.6 干扰对定位精度的影响分析··································································156
    3.4.7 NLOS 环境下的定位算法研究································································164
    3.4.8 移动目标的跟踪定位算法研究·······························································174
    参考文献··········································································································202
    第4 章 惯性导航技术····················································································210
    4.1 概述·········································································································210
    4.1.1 基本概念··························································································210
    4.1.2 惯性导航技术的发展状况·····································································211
    4.2 惯性导航基础·····························································································212
    4.2.1 地球形状和重力模型···········································································212
    4.2.2 哥氏力和比力····················································································217
    4.2.3 常用坐标系·······················································································218
    4.2.4 坐标变换与姿态·················································································221
    4.3 捷联式惯性导航方法····················································································231
    4.3.1 SINS 的工作原理················································································232
    4.3.2 捷联式定位定姿系统初始定向工作原理···················································232
    4.4 惯性导航应用·····························································································237
    4.4.1 在舰船导航中的应用···········································································238
    4.4.2 在行人定位中的应用···········································································238
    4.4.3 在航空领域的应用··············································································238
    4.4.4 在导弹制导中的应用···········································································238
    4.4.5 在电子行业的应用··············································································239
    4.5 惯性导航技术的最新进展及未来发展趋势·························································239
    4.5.1 惯性导航技术的最新进展·····································································239
    4.5.2 惯性导航技术的未来发展趋势·······························································239
    参考文献··········································································································240
    第5 章 机器人SLAM 技术·········································································242
    5.1 SLAM 算法介绍··························································································242
    5.1.1 基于特征点法的SLAM 算法··································································244
    5.1.2 基于直接法的SLAM 算法·····································································247
    5.1.3 融合特征点法和直接法的SLAM 算法······················································250
    5.1.4 融合视觉信息和IMU 信息的SLAM 算法·················································252
    5.1.5 动态场景下的SLAM 算法·····································································255
    5.2 SLAM 技术发展中存在的问题与对策·······························································257
    5.3 SLAM 技术发展前沿····················································································261
    5.4 语义SLAM 技术·························································································263
    5.4.1 语义信息用于特征选择········································································264
    5.4.2 语义信息用于动态SLAM ·····································································266
    5.4.3 语义信息用于单目SLAM 的尺度恢复······················································270
    5.4.4 语义信息用于long-term 定位·································································271
    5.4.5 语义信息用于提高定位精度··································································273
    5.4.6 SLAM 的动态地图和语义问题·······························································275
    5.5 点线SLAM 系统·························································································281
    5.5.1 VSLAM 中的线段特征提取···································································283
    5.5.2 基于点线综合特征的VSLAM 系统·························································295
    5.6 SLAM 技术应用场景····················································································304
    5.6.1 室内机器人·······················································································305
    5.6.2 方量计算··························································································306
    5.6.3 自动驾驶··························································································311
    参考文献··········································································································312
    第6 章 多源信息融合算法及其在组合导航中的应用·································317
    6.1 基于KF 的状态估计研究现状·········································································318
    6.1.1 KF 研究现状······················································································318
    6.1.2 不确定系统的KF 研究现状···································································319
    6.1.3 基于KF 的组合导航研究现状································································322
    6.2 DKF 算法··································································································324
    6.2.1 DKF 算法简介····················································································324
    6.2.2 自适应快速DKF 算法··········································································324
    6.2.3 自适应快速弱敏EKF 算法····································································328
    6.2.4 自适应快速弱敏UKF算法···········································································331
    6.3 SKF 算法及其在组合导航中的应用·································································344
    6.3.1 SKF 算法··························································································344
    6.3.2 Consider 集合KF 算法·········································································349
    6.3.3 部分强跟踪Consider SDREF 算法及其应用···············································359
    参考文献··········································································································372
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    前     言

    随着科技的飞速发展,移动机器人已经广泛应用于工业、农业、军事、医疗等多个领
    域,成为现代科技的重要组成部分。移动机器人的自主导航与定位技术是实现其智能化和
    自动化的关键,如何在复杂环境中实现精确的导航与定位,成了当前机器人研究的热点和
    难点问题。本书旨在系统地总结和介绍移动机器人在无线导航与定位技术方面的最新研究
    成果及应用经验,以便为读者提供全面、深入的技术参考。
    全书共6 章,各章节内容概述如下:
    第1 章从移动机器人概念出发,介绍了移动机器人发展的历史和现状。移动机器人是
    指能够在不依赖外部环境的情况下,通过自身携带的传感器和控制系统,实现自主移动和
    操作的机器人系统。随着传感器技术、计算机技术和人工智能技术的进步,移动机器人技
    术得到了迅速的发展和广泛应用。本章详细讨论了移动机器人的关键技术,包括传感器技
    术、控制技术、路径规划技术和导航定位技术。特别是介绍了导航定位技术的概念、分类
    及其发展趋势,帮助读者建立对导航定位技术的整体认识。
    导航定位技术是移动机器人实现自主导航的核心技术之一。第2 章详细介绍了几种常
    用的导航定位技术,包括卫星导航定位技术、同步定位与地图构建(SLAM)技术、Wi-
    Fi 定位技术、蓝牙定位技术、ZigBee 定位技术、RFID 定位技术、地磁定位技术、智能天
    线定位技术、超声波导航定位技术和红外线定位技术。对每种技术的工作原理、系统组
    成、优缺点及其在实际应用中的表现都进行了深入剖析,为读者提供了全面的技术参考。
    超宽带(UWB)技术是近年来在室内定位领域兴起的一种高精度定位技术。第3 章
    详细介绍了UWB 技术的定义、特点及其在室内定位中的应用。通过对UWB 脉冲的产生
    和调制技术、接收机设计、室内定位算法等内容的深入介绍,读者可以系统了解UWB 技
    术的实现方法和应用场景。本章特别对基于UWB 信道模型的定位算法、非视距环境下的
    定位算法及移动目标的定位跟踪算法进行了详细探讨,展示了UWB 技术在复杂环境中的
    应用潜力。
    惯性导航技术是利用惯性传感器(加速度计和陀螺仪)测量机器人运动状态,实现自
    主导航的一种技术。第4 章从惯性导航的基本概念和发展状况出发,详细介绍了惯性导航
    的基础理论,包括地球形状和重力模型、哥氏力和比力、常用坐标系及坐标变换与姿态等
    内容。捷联惯性导航方法是本章的重点,读者可以通过了解捷联惯性导航系统的工作原理
    和初始定向工作原理,掌握惯性导航技术的实现方法。本章还介绍了惯性导航技术在舰船
    导航、行人定位、航空、导弹制导及电子行业中的应用,最后介绍了惯性导航技术的最新
    进展及未来发展趋势。
    SLAM 技术是移动机器人实现自主导航与定位的核心技术之一。第5 章详细介绍了
    SLAM 系统的基本状况、常用SLAM 算法及其发展中存在的问题与对策。基于特征点法
    的SLAM 算法、基于直接法的SLAM 算法及融合视觉和IMU 的SLAM 算法是本章的重
    点内容。语义SLAM 技术是SLAM 研究的前沿领域,本章详细讨论了语义信息在SLAM
    中的应用,包括用于特征选择、动态SLAM、单目SLAM 的尺度恢复及long-term 定位等
    方面。本章还介绍了点线SLAM 系统算法,展示了SLAM 技术在提升定位精度方面的最
    新研究进展。
    多源信息融合算法是提升导航定位精度和鲁棒性的有效方法。第6 章详细介绍了基于
    卡尔曼滤波的状态估计、多种弱敏卡尔曼滤波算法、Consider 卡尔曼滤波算法及其在组
    合导航中的应用。通过对这些算法的深入分析,读者可以了解如何在复杂环境中,通过融
    合多源信息实现高精度、高可靠性的导航定位。本章还探讨了不确定系统下的卡尔曼滤波
    及其应用,为读者展示了多源信息融合算法在应对导航定位挑战中的重要作用。
    本书不仅涵盖了当前主流的导航定位技术,还深入探讨了新兴技术和前沿研究,力求
    为读者提供最新的技术发展状况和趋势。通过阅读本书,读者可以全面掌握移动机器人无
    线导航定位技术的理论基础和前沿技术,为未来的研究与开发工作打下坚实的基础。
    本书由赵红梅负责组织,其主要撰写了第1 章、第3 章、第6 章的部分内容,王云飞
    参与了第3 章内容的撰写,焦玉召参与了第2 章内容的撰写,王晓雷参与了第4 章内容的
    撰写,丁国强参与了第5 章内容的撰写,娄泰山参与了第6 章内容的撰写,并得到了郑州
    轻工业大学无线导航定位技术与装备团队和河南省“超宽带无线通信技术”院士工作站研
    究团队各位老师及研究生的大力支持。书中也引用了一些作者的论著及研究成果,在此对
    他们表示深深的谢意。本书由中国工程科技发展战略河南研究院重点咨询项目——“新一
    代信息技术对河南省机器人产业发展支撑与推进战略研究”项目资助,项目编号
    2021HENZDB01,在此对项目管理方的支持表示感谢。
    在本书的撰写过程中,我们尽力做到内容详实、结构清晰,但由于导航定位技术发展
    迅速,书中难免存在不足之处,恳请读者批评指正。我们希望本书能够对读者有所帮助,
    从而为推动移动机器人技术的发展贡献一份力量。
    著 者
    展开

    作者简介

    赵红梅,女,教授,信息与通信工程专业工学博士,硕士生导师,联合博士导师,郑州轻工业学院无线导航定位团队负责人,河南省"超宽带无线通信技术”及郑州市"UWB实时定位系统”院士工作站院士助手,河南省优秀硕士学位论文指导教师,河南省仪器仪表学会常务理事,副秘书长,河南省中文信息学会福利实战;长期从事微带天线设计、超宽带无线通信技术等方向的研究;获河南省科技进步奖二等奖4项,厅级科技成果一等奖6项,通过省级科技成果鉴定14项,授权国家发明专利9项,软件著作权3件,主持及参与国家和省级项目12项,出版专著1部,参编教材1部,出版研究报告1部,发表论文40多篇。 目前研究方向:微带天线设计、超宽带信号电波传播特性研究、超宽带室内定位技术研究、阵列信号处理
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