Journal of Shandong University(Engineering Science) ›› 2021, Vol. 51 ›› Issue (5): 16-31.doi: 10.6040/j.issn.1672-3961.0.2021.168

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Review on development of simultaneous localization and mapping technology

Jianqing WU(),Xiuguang SONG*()   

  1. School of Qilu Transportation, Shandong University, Jinan 250002, Shandong, China
  • Received:2021-04-12 Online:2021-10-20 Published:2021-09-29
  • Contact: Xiuguang SONG E-mail:jianqingwusdu@sdu.edu.cn;songxiuguang@sdu.edu.cn

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Abstract:

As a hot spot in the field of intelligent transportation, simultaneous localization and mapping (SLAM) technology is the key to autonomous path planning for self-driving vehicles. This review focused on four parts with introduction of sensors related to SLAM technology, localization, mapping, and multi-sensor integration. Each step of realization for SLAM technology was introduced from advantages and disadvantages, range of application, probability algorithm, types of map, and integration methods. Based on the investigation of relevant researches about multi-sensor integration, common problems of SLAM technology were analyzed, future development trend and practical engineering application of SLAM technology were prospected.

Key words: SLAM, localization, mapping, multi-sensor fusion, deep learning, camera, lidar

CLC Number: 

  • TQ028

Fig.1

Process of SLAM"

Fig.2

Three eras of development of SLAM"

Fig.3

Flow chart of estimation for particle filter"

Table 1

Table of advantages and disadvantages for each sensor"

传感器类型 优点 缺点
相机 单目相机 操作简单、成本较低 无法采集深度信息
多目相机 可获取运动与静止状态下目标的深度信息 标定与计算过程相对复杂、计算量较大
深度相机 可获取物体的色彩与深度信息、数据采集速度快、数据量更丰富 易受视场角与分辨率影响
激光雷达 2D激光雷达 适用于平面信息采集 感知数据缺乏高度信息，难以成像
3D激光雷达 感知数据具备目标的高度、距离信息，能够还原物体形状，可实现全天候工作 价格昂贵、易受雨雪雾霾等天气影响
惯性测量单元 采集目标加速度、姿态角信息 易产生累积误差
毫米波雷达 对于雨雪雾霾等穿透力强 数据精度低、多冲波段下工作性能会大幅降低
超声波雷达 耗能缓慢、在介质中传播距离远、价格便宜 传输速度极易受天气影响、传输速度相对较慢
红外热成像仪 信息感受更直观、不受电磁影响、作用距离相对较远、全天候环境感知 成本高、不能穿透玻璃制品、存在图片分辨率低与信息对比度小的问题

Table 2

Table of advantages and disadvantages for each map"

地图表示类型 优点 缺点
拓扑地图 适用于范围广且障碍物类型较少的场景、占用内存小、计算效率高、路径规划高效 路径规划最优性差、相似物体分辨准确度低
几何信息地图 简化环境信息、障碍物辨识更直观、目标提取更方便 广域环境中数据精度低、计算量大
栅格地图 不受环境地形影响、感知数据易保存与维护 保存数据过多会导致信息更新难度加大、目标识别效果变差

Fig.4

Map based on LiDAR-SLAM"

1 赵光辉. 我国"互联网+"交通服务的演进与政策[J]. 中国流通经济, 2016, 30 (3): 39- 48.
doi: 10.3969/j.issn.1007-8266.2016.03.006
ZHAO Guanghui . Evolution and policy of "Internet+" transportation service in China[J]. China′s Circulation Economy, 2016, 30 (3): 39- 48.
doi: 10.3969/j.issn.1007-8266.2016.03.006
2 ILGEN Elke , KARFICH Natascga , LEVSEN Karsten , et al. Aromatic hydrocarbons in the atmospheric enviro-nment: part I: indoor versus outdoor sources, the influence of traffic[J]. Atmospheric Environment, 2001, 35 (7): 1235- 1252.
doi: 10.1016/S1352-2310(00)00388-5
3 CADENA Cesar , CARLONE Luca , CARRILLO Henry , et al. Past, present, and future of simultaneous localization and mapping: toward the robust-perception age[J]. IEEE Transactions on Robotics, 2016, 32 (6): 1309- 1332.
doi: 10.1109/TRO.2016.2624754
4 周彦, 李雅芳, 王冬丽, 等. 视觉同时定位与地图创建综述[J]. 智能系统学报, 2018, 13 (1): 97- 106.
doi: 10.11992/tis.201703006
ZHOU Yan , LI Yafang , WANG Dongli , et al. Overview of visual simultaneous positioning with map creation[J]. Journal of Intelligent Systems, 2018, 13 (1): 97- 106.
doi: 10.11992/tis.201703006
5 《中国公路学报》编辑部. 中国交通工程学术研究综述·2016[J]. 中国公路学报, 2016, 29 (6): 1- 161.
doi: 10.3969/j.issn.1001-7372.2016.06.001
Editorial Department of China Journal of Highway . Review of traffic engineering research in China 2016[J]. China Journal of Highway and Transport, 2016, 29 (6): 1- 161.
doi: 10.3969/j.issn.1001-7372.2016.06.001
6 曹风魁, 庄严, 闫飞, 等. 移动机器人长期自主环境适应研究进展和展望[J]. 自动化学报, 2020, 46 (2): 205- 221.
CAO Fengkui , ZHUANG Yan , YAN Fei , et al. Research progress and prospect of long-term autonomous environmental adaptation of mobile robots[J]. Acta Automatica Sinica, 2020, 46 (2): 205- 221.
7 祝朝政, 何明, 杨晟, 等. 单目视觉里程计研究综述[J]. 计算机工程与应用, 2018, 54 (7): 20- 28.
doi: 10.3778/j.issn.1002-8331.1712-0279
ZHU Chaozheng , HE Ming , YANG Sheng , et al. A review of monocular vision odometer research[J]. Computer Engineering and Applications, 2018, 54 (7): 20- 28.
doi: 10.3778/j.issn.1002-8331.1712-0279
8 谭静, 赵健康, 崔超. 基于双目视觉与IMU的组合导航算法[J]. 计算机工程与设计, 2021, 42 (2): 442- 448.
TAN Jing , ZHAO Jiankang , CUI Chao . Integrated navigation algorithm based on binocular vision and IMU[J]. Computer Engineering and Design, 2021, 42 (2): 442- 448.
9 ESSMAEEL Kyis, GALLO Luigi, DAMIANI Ernesto, et al. Temporal denoising of kinect depth data[C]//Proceedings of 8th International Conference on Signal Image Technology & Internet Based Systems. Sorrento, Italy: IEEE, 2013: 47-52.
10 LIAO Ziwei , WANG Wei , QI Xianyu , et al. RGBD object SLAM using quadrics for indoor environments[J]. Sensors, 2020, 20 (18): 1- 34.
doi: 10.1109/JSEN.2020.3014328
11 HENRY Peter , KRAININ Michael , HERBST Evan , et al. RGBD mapping: using depth cameras for dense 3D modeling of indoor environments[J]. The International Journal of Robotics Research, 2012, 31 (5): 647- 663.
doi: 10.1177/0278364911434148
12 DRYANOVSKI Ivan, VALENTI Roberto G, XIAO Jizhong. Fast visual odometry and mapping from RGBD data[C]//Proceedings of 2013 IEEE International Conference on Robotics and Automation. Karlsruhe, Germany: IEEE, 2013: 2305-2310.
13 杨明, 王宏, 何克忠, 等. 基于激光雷达的移动机器人环境建模与避障[J]. 清华大学学报(自然科学版), 2000, 40 (7): 112- 116.
doi: 10.3321/j.issn:1000-0054.2000.07.030
YANG Ming , WANG Hong , HE Kezhong , et al. Environment modeling and obstacle avoidance of mobile robot based on LiDAR[J]. Journal of Tsinghua University (Natural Science), 2000, 40 (7): 112- 116.
doi: 10.3321/j.issn:1000-0054.2000.07.030
14 WU Jianqing, XU Hao, ZHENG Jianying. Automatic background filtering and lane identification with roadside LiDAR data[C]//Proceedings of 2017 IEEE 20th International Conference on Intelligent Transportation Systems. Yokohama, Japan: IEEE, 2017: 6.
15 PATERNAIN Santiago , TAILANIAN Matias , CANETTI Rafael . Calibration of an inertial measurement unit[J]. International Applied Mechanics, 2017, 53 (2): 1- 6.
16 秦志斌, 王慧娟. 智慧高速毫米波雷达应用浅析[J]. 中国交通信息化, 2021, (3): 130- 131.
QIN Zhibin , WANG Huijuan . Application analysis of intelligent high speed millimeter wave radar[J]. Traffic Informatization in China, 2021, (3): 130- 131.
17 魏琴, 谷谢天, 陈平易. 智能汽车技术及环境感知传感器初探[J]. 内燃机与配件, 2019, (2): 174- 175.
doi: 10.3969/j.issn.1674-957X.2019.02.086
WEI Qin , GU Xietian , CHEN Pingyi . A preliminary study on intelligent vehicle technology and environmental sensing sensor[J]. Internal Combustion Engine and Accessories, 2019, (2): 174- 175.
doi: 10.3969/j.issn.1674-957X.2019.02.086
18 蔡毅, 王岭雪. 红外成像技术中的9个问题[J]. 红外技术, 2013, 35 (11): 671- 682.
doi: 10.11846/j.issn.1001_8891.201311001
CAI Yi , WANG Lingxue . Nine problems in infrared imaging technology[J]. Infrared Technology, 2013, 35 (11): 671- 682.
doi: 10.11846/j.issn.1001_8891.201311001
19 张本法, 孟祥萍, 岳华. 移动机器人定位方法概述[J]. 山东工业技术, 2014, (22): 250.
ZHANG Benfa , MENG Xiangping , YUE Hua . Overview of localization methods for mobile robots[J]. Shandong Industrial Technology, 2014, (22): 250.
20 高云峰, 周伦, 吕明睿, 等. 自主移动机器人室内定位方法研究综述[J]. 传感器与微系统, 2013, 32 (12): 1- 5.
doi: 10.3969/j.issn.1000-9787.2013.12.001
GAO Yunfeng , ZHOU Lun , LV Mingrui , et al. A review of indoor positioning methods forautonomous mobile robots[J]. Sensors and Microsystems, 2013, 32 (12): 1- 5.
doi: 10.3969/j.issn.1000-9787.2013.12.001
21 纪嘉文, 杨明欣. 一种基于多传感融合的室内建图和定位算法[J]. 成都信息工程学院学报, 2018, 33 (4): 400- 407.
doi: 10.16836/j.cnki.jcuit.2018.04.009
JI Jiawen , YANG Mingxin . An indoor mapping and positioning algorithm based on multi-sensor fusion[J]. Journal of Chengdu Institute of Information Engineering, 2018, 33 (4): 400- 407.
doi: 10.16836/j.cnki.jcuit.2018.04.009
22 MEINLSCHMIDT Thomas, ASCHEMANN Harald, BUTT Saif. Cascaded backstepping control of a Duocopter including disturbance compensation by unscented Kalman filtering[C]// Proceedings of 2014 Inter-national Conference on Control, Decision and Information Technologies. Metz, France: IEEE, 2014: 315-320.
23 中国科学院电子学研究所, 中国科学院文献情报中心. 自动化技术、计算机技术[J]. 中国无线电电子学文摘, 2011, 27 (1): 161- 238.
Institute of Electronics, Chinese Academy of Sciences , Literature and Information Center of Chinese Academy of Sciences . Automation technology, computer technology[J]. China Radio Electronics Abstracts, 2011, 27 (1): 161- 238.
24 熊敏君, 卢惠民, 熊丹, 等. 基于单目视觉与惯导融合的无人机位姿估计[J]. 计算机应用, 2017, 37 (增刊2): 127- 133.
XIONG Minjun , LU Huimin , XIONG Dan , et al. UAV pose estimation based on monocular vision and inertial navigation fusion[J]. Computer Application, 2017, 37 (Suppl. 2): 127- 133.
25 吕太之, 周武, 赵春霞. 一种改进的UKF-SlAM算法[J]. 中北大学学报(自然科学版), 2018, 39 (6): 717- 725.
doi: 10.3969/j.issn.1673-3193.2018.06.014
LV Taizhi , ZHOU Wu , ZHAO Chunxia . An improved UKF-SLAM algorithm[J]. Journal of North University of China (Natural Science Edition), 2018, 39 (6): 717- 725.
doi: 10.3969/j.issn.1673-3193.2018.06.014
26 KIMURA Aritoshi, ARIZONO Ikuo, OHTA Hiroshi. A back-propagation algorithm based on the extended Kalman filter[C]//Proceedings of 1993 International Joint Conference on Neural Networks. Nagoya, Japan: IJC, 1993: 1669-1672.
27 SMITH Randall , SELF Matthew , CHEESEMAN Peter . Estimating uncertain spatial relationships in robotics[J]. Machine Intelligence & Pattern Recognition, 1988, 5 (5): 435- 461.
28 YAVUZ Slrma, KURT Zeyneb, BICER M Serdar. Simultaneous localization and mapping using extended Kalman filter[C]//Proceedings of 2009 IEEE 17th Signal Processing and Communications Applications Conference. Antalya, Turkey: IEEE, 2009: 7000-7033.
29 王盼盼, 黄宜庆. 基于时变调节因子的移动机器人EKF-SLAM算法[J]. 安徽工程大学学报, 2017, 32 (5): 46- 50.
doi: 10.3969/j.issn.2095-0977.2017.05.010
WANG Panpan , HUANG Yiqing . EKF-SLAM algorithm for mobile robots based on time-varying regulator[J]. Journal of Anhui Engineering University, 2017, 32 (5): 46- 50.
doi: 10.3969/j.issn.2095-0977.2017.05.010
30 付强, 张宏静, 赵建伟, 等. 移动机器人SLAM改进算法的分析与实现[J]. 兵工自动化, 2018, 37 (9): 86- 89.
doi: 10.7690/bgzdh.2018.09.021
FU Qiang , ZHANG Hongjing , ZHAO Jianwei , et al. Analysis and implementation of improved SLAM algorithm for mobile robots[J]. Ordnance Automation, 2018, 37 (9): 86- 89.
doi: 10.7690/bgzdh.2018.09.021
31 刘沛丰, 王坚. 一种基于抗差EKF的移动机器人定位技术[J]. 计算机科学, 2017, 44 (增刊1): 115- 118.
LIU Peifeng , WANG Jian . A mobile robot localization technology based on robust EKF[J]. Computer Science, 2017, 44 (Suppl.1): 115- 118.
32 程璐, 黄宜庆. 基于Cholesky分解的改进自适应EKF-SLAM算法[J]. 安徽工程大学学报, 2020, 35 (2): 11- 20.
CHENG Lu , HUANG Yiqing . Improved adaptive EKF-SLAM algorithm based on cholesky decomposition[J]. Journal of Anhui Engineering University, 2020, 35 (2): 11- 20.
33 CHATTERJEE Amitava , MATSUNO Fumitoshi . A neuro-fuzzy assisted extended Kalman filter-based approach for simultaneous localization and mapping (SLAM) problems[J]. IEEE Transactions on Fuzzy Systems, 2007, 15 (5): 984- 997.
doi: 10.1109/TFUZZ.2007.894972
34 PIGA Nicola A. , BOTTAREL Fabrizio , FANTACCI Claudio . MaskUKF: an instance segmentation aided unscented Kalman filter for 6D object pose and velocitytracking[J]. Frontiers in Robotics and AI, 2021, 8 (38): 1- 17.
35 孙海波, 童紫原, 唐守锋, 等. 基于卡尔曼滤波与粒子滤波的SLAM研究综述[J]. 软件导刊, 2018, 17 (12): 1- 3.
SUN Haibo , TONG Ziyuan , TANG Shoufeng , et al. Review of SLAM research based on Kalman filter and particle filter[J]. Software Guide, 2018, 17 (12): 1- 3.
36 LIU Qin , LIU Zheng , LIU Yunfo . Nonorthogonal problem in iterated unscented Kalman filter for passive tracking[J]. IEEE Transactions on Electrical and Electronic Engineering, 2013, 8 (4): 415- 419.
doi: 10.1002/tee.21873
37 CHEN Yunqiang, HUANG Thomas, RUI Yong. Parametric contour tracking using unscented Kalmanfilter[C]//Proceedings of 2002 International Conference on Image Processing: Vol Ⅲ. Beijing: IEEE, 2002: 613-616.
38 刘艳, 程诚, 裴少婧. 鲁棒自适应无迹卡尔曼滤波的SLAM算法[J]. 电光与控制, 2019, 26 (8): 12- 16.
doi: 10.3969/j.issn.1671-637X.2019.08.003
LIU Yan , CHENG Cheng , PEI Shaojing . A SLAM algorithm for robust adaptive untraced Kalman filter[J]. Electro-Optical and Control, 2019, 26 (8): 12- 16.
doi: 10.3969/j.issn.1671-637X.2019.08.003
39 QI Ming. An improved particle filter SLAM algorithm for AGVs[C]//Proceedings of 20 IEEE 6th Int-ernational Conference on Control Science and Systems Engineering. Beijing: IEEE, 2020: 27-31.
40 GORDON N J , SALMONDD J , SMITHA F M . Novel-approach to nonlinear non-gaussian Bayesian state estimation[J]. IEEE Proceedings: F Radar and Signal Processing, 1993, 140 (2): 107- 113.
doi: 10.1049/ip-f-2.1993.0015
41 周武, 赵春霞. 一种改进的边缘粒子滤波slam方法[J]. 华中科技大学学报(自然科学版), 2008, (增刊1): 181- 185.
ZHOU Wu , ZHAO Chunxia . An improved edge particle filtering SLAM method[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2008, (Suppl.1): 181- 185.
42 吴培良, 孔亮, 段亮亮, 等. 一种基于提议分布选择的改进边缘粒子滤波算法[J]. 小型微型计算机系统, 2016, 37 (2): 381- 384.
doi: 10.3969/j.issn.1000-1220.2016.02.036
WU Peiliang , KONG Liang , DUAN Liangliang , et al. An improved edge particle filtering algorithm based on proposed distribution selection[J]. Journal of Small and Micro Computer Systems, 2016, 37 (2): 381- 384.
doi: 10.3969/j.issn.1000-1220.2016.02.036
43 DELLAERT Frank, FOX Dieter, BURGARD Wolfram, et al. Monte Carlo localization for mobile robots[C]//Proceedings of 1999 IEEE International Conference on Robotics and Automation. New York, USA: IEEE, 1999: 1322-1328.
44 石雪军, 纪志成. 基于改进粒子滤波的射频识别室内跟踪算法[J]. 计算机工程, 2015, 41 (11): 308- 313.
doi: 10.3969/j.issn.1000-3428.2015.11.053
SHI Xuejun , JI Zhicheng . Indoor tracking algorithm of radio frequency identification based on improved particle filter[J]. Computer Engineering, 2015, 41 (11): 308- 313.
doi: 10.3969/j.issn.1000-3428.2015.11.053
45 武斌, 田清. 改进无迹粒子滤波的室内移动目标定位[J]. 传感器与微系统, 2021, 40 (3): 153- 156.
WU Bin , TIAN Qing . Indoor moving target localization algorithm based on improved untraceable particle filtering[J]. Transducers and Microsystems, 2021, 40 (3): 153- 156.
46 MONTEMERLO Michael, THRUN Sebastian. Simultaneous localization and mapping with unknown data association using Fast SLAM[C]//Proceedings of 2003 IEEE International Conference on Robotics and Automation. Taipei, China: IEEE, 2003: 1985-1991.
47 THRUN Sebastian, MONTEMARLO Michael, KOLLER Daphne, et al. Fast SLAM: a factored solution to the simultaneous localization and mapping problem[C]//Proceedings of AAAI National Conference on Artificial Intelligence. Edmonton, Canada: IEEE, 2002: 240-248.
48 BEESON Patrick , MODAYIL Joseph , KUIPERS Benjamin . Factoring the apping problem: mobile robot map-building in the hybrid spatial semantic hierarchy[J]. International Journal of Robotics Research, 2010, 29 (4): 428- 459.
doi: 10.1177/0278364909100586
49 崔杨. 智能移动机器人同步定位与地图构建算法研究[J]. 电子世界, 2013, (23): 113- 114.
doi: 10.3969/j.issn.1003-0522.2013.23.088
CUI Yang . Review on synchronous localization and map construction algorithm of intelligent mobile robot[J]. Electronic World, 2013, (23): 113- 114.
doi: 10.3969/j.issn.1003-0522.2013.23.088
50 KOLHATKAR Chinmay, WAGLE Kranti. Review of SLAM algorithms for indoor mobile robot with LIDAR and RGBD camera technology[C]//Proceedings of ICEEE 2020. Antalya, Turkey: IEEE, 2021: 397-409.
51 李万莉, 王文佳. 基于Hough变换的激光几何特征地图提取方法[J]. 机电一体化, 2018, 24 (7): 3- 7.
LI Wanli , WANG Wenjia . Geometric feature map extraction for laser SLAM based on hough transform[J]. Mechatronics, 2018, 24 (7): 3- 7.
52 ARSHAD Saba , KIM Gon-Woo . Role of deep learning in loop closure detection for visual and lidar SLAM: a survey[J]. Sensors, 2021, 21 (4): 17.
53 DINH Nam, KIM Gon-Woo. Solid-state LiDAR based-SLAM: a concise review and application[C]//Proceedings of 2021 IEEE International Conference on Big Data and Smart Computing. Jeju, Korea: IEEE, 2021: 302-305.
54 NUTZI Gabriel , WEISS Stephan , SCARAMUZZA Davide . Fusion of IMU and vision for absolute scale estimation in monocular SLAM[J]. Journal of Intelligent & Robotic Systems, 2011, 61 (1/2/3/4): 287- 299.
55 NIKOLIC Janosch, REHDER Joern, BURRI Michael. A synchronized visual-inertial sensor system with FPGA pre-processing for accurate real-time SLAM[C]//Proceedings of 2014 IEEE International Conference on Robotics and Automation. Hong Kong, China: IEEE, 2014: 431-437.
56 CONCHA Alejo, LOIANNO Giuseppe, KUMAR Vijay, et al. Visual-inertial direct SLAM[C]//Proceedings of 2016 IEEE International Conference on Robotics and Automation. Stockholm, Sweden: IEEE, 2016: 1331-1338.
57 RAUL Mur-Artal , TARDOS Juan D . Visual-inertial monocular SLAM with map reuse[J]. IEEE Robotics and Automation Letters, 2017, 2 (2): 796- 803.
doi: 10.1109/LRA.2017.2653359
58 QIN Tong, LI Peiliang, SHEN Shaojie. Relocalization, global optimization and map merging for monocular visual-inertial SLAM[C]//Proceedings of 2018 IEEE International Conference on Robotics and Automation. Brisbane, Australia: IEEE, 2018: 1197-1204.
59 潘林豪, 田福庆, 应文健, 等. 融合双目视觉与惯导信息的高效视觉里程计算法[J]. 计算机应用研究, 2021, 38 (6): 1739- 1743.
doi: 10.19734/j.issn.1001-3695.2020.08.0188
PAN Linhao , TIAN Fuqing , YING Wenjian , et al. An efficient vision odometry method based on binocular vision and IMU information[J]. Application Research of Computers, 2021, 38 (6): 1739- 1743.
doi: 10.19734/j.issn.1001-3695.2020.08.0188
60 种一帆, 冀杰, 宫铭钱, 等. 半直接法与IMU融合的双目视觉里程计[J]. 西南师范大学学报(自然科学版), 2021, 46 (2): 112- 120.
ZHONG Yifan , JI Jie , GONG Mingqian , et al. Binocular vision odometer with semi-direct method and IMU fusion[J]. Journal of Southwest Normal University (Natural Science Edition), 2021, 46 (2): 112- 120.
61 BLOESCH Michael, OMARI Sammy, HUTTER Marco, et al. Robust visual inertial odometry using a direct EKF-based approach[C]//Proceedings of 2015 IEEE/RSI International Conference on Intelligent Robots and Systems. Hamburg, Germany: IEEE, 2015: 298-304.
62 SCHNEIDER Thomas, DYMCZYK Marcin, FEHR Marius, et al. Maplab: an open framework for research in visual-inertial mapping and localization[J]. 2017, 3(3): 1418-1425.
63 慈文彦, 黄影平, 胡兴. 视觉里程计算法研究综述[J]. 计算机应用研究, 2019, 36 (9): 2561- 2568.
CI Wenyan , HUANG Yingping , HU Xing . Review of visual mileage calculation[J]. Application Research of Computers, 2019, 36 (9): 2561- 2568.
64 YE Haoyang, CHEN Yuying, LIU Ming. Tightly coupled 3D Lidar inertial odometry and mapping[C]//Proceedings of the 2019 International Conference on Robotics and Automation. Montreal, Canada: ICRA, 2019: 3144-3150.
65 庞帆, 危双丰, 师现杰, 等. 激光雷达惯导耦合的里程计与建图方法[J]. 计算机应用研究, 2021, 38 (6): 1- 7.
PANG Fan , WEI Shuangfeng , SHI Xianjie , et al. Odometer and mapping method for lidar inertial navigation coupling[J]. Computer Application Research, 2021, 38 (6): 1- 7.
66 张艳国, 李擎. 基于惯性测量单元的激光雷达点云融合方法[J]. 系统仿真学报, 2018, 30 (11): 4334- 4339.
ZHANG Yanguo , LI Qing . LiDAR point cloud fusion method based on inertial measurement unit[J]. Journal of System Simulation, 2018, 30 (11): 4334- 4339.
67 GENEVA Patrick, ECKENHOFF Kevin, YANG Yulin, et al. LIPS: LiDAR-inertial 3D plane SLAM[C]//Proceedings of 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems. Madrid, Spain: IEEE, 2018: 123-130.
68 LV Bin , XU Hao , WU Jianqing , et al. Revolution and rotation-based method for roadside LiDAR data integration[J]. Optics & Laser Technology, 2019, 119, 105571.
69 WU Jianqing , XU Hao , LIU Wei . Points registration for roadside LiDAR sensors[J]. Transportation Research Record, 2019, 2673 (9): 627- 639.
doi: 10.1177/0361198119843855
70 YUE Rui , XU Hao , WU Jianqing , et al. Data registration with ground points for roadside LiDAR sensors[J]. Remote Sensing, 2019, 11 (11): 16.
71 NEWMAN P, COLE D, HO K. Outdoor SLAM using visual appearance and laser ranging[C]//Proceedings of 2006 IEEE International Conference on Robotics and Automation. Orlando, USA: IEEE, 2006: 1180-1187.
72 LIN Kuenhan , CHANG Chunhua , DOPFER Andreas , et al. Mapping and localization in 3D environments using a 2D laser scanner and a stereo camera[J]. Journal of Information Science and Engineering, 2012, 28 (1): 131- 144.
73 WEN Chenglu , QIN Ling , ZHU Qingyuan , et al. Three-dimensional indoor mobile mapping with fusion of two-dimensional laser scanner and RGBD camera data[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11 (4): 843- 847.
doi: 10.1109/LGRS.2013.2279872
74 SHIN Y S, PARK Y S, KIM Ayoung. Direct visual SLAM using sparse depth for camera-LiDAR system[C]// Proceedings of 2018 IEEE International Conference on Robotics and Automation. Brisbane, Australia: IEEE, 2018: 5144-5151.
75 ZHANG Ji , SINGH Sanjiv . Low-drift and real-time lidar odometry and mapping[J]. Autonomous Robots, 2017, 41 (2): 401- 416.
doi: 10.1007/s20514-016-9548-2
76 CHEN Mengxiao, YANG Shaowu, YI Xiaodong, et al. Real-time 3D mapping using a 2D laser scanner and IMU-aided visual SLAM[C]//Proceedings of the 2017 IEEE International Conference on Real-time Computing and Robotics. Okinawa, Japan: IEEE, 2017: 207-302.
77 HUANG Kaihong, STACHNISS Cyrill. Joint ego-motion estimation using a laser scanner and a monocular camera through relative orientation estimation and 1-DoF ICP[C]//Proceedings of 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems. Madrid, Spain: IEEE, 2018: 671-676.
78 DING Xiaqing, WANG Yue, LI Dongxuan, et al. Laser map aided visual inertial localization in changing environment[C]// Proceedings of 25th IEEE/RSJ International Conference on Intelligent Robots and Systems. Madrid, Spain: IEEE, 2018: 4794-4801.
79 ZHANG Ji , SINGH Sanjiv . Laser-visual-inertial odometry and mapping with high robustness and low drift[J]. Journal of Field Robotics, 2018, 35 (8): 1242- 1264.
doi: 10.1002/rob.21809https://onlinelibrary.wiley.com/doi/abs/10.1002/rob.21809
80 肖军浩, 施成浩, 黄开宏, 等. 单目相机-3维激光雷达的外参标定及融合里程计研究[J]. 机器人, 2021, 43 (1): 17- 28.
doi: 10.13973/j.cnki.robot.200030
XIAO Junhao , SHI Chenghao , HUANG Kaihong , et al. Study on external reference calibration and fusion odometer of monocular camera-3D lidar[J]. The Robot, 2021, 43 (1): 17- 28.
doi: 10.13973/j.cnki.robot.200030
81 郭安, 周洲, 祝小平, 等. 基于EKF算法的太阳能无人机低成本飞控状态估计[J]. 控制与决策, 2020, 35 (10): 2415- 2423.
doi: 10.13195/j.kzyjc.2019.0091
GUO An , ZHOU Zhou , ZHU Xiaoping , et al. Low-cost flight control state estimation of solar unmanned aerial vehicle based on EKF algorithm[J]. Control and Decision Making, 2020, 35 (10): 2415- 2423.
doi: 10.13195/j.kzyjc.2019.0091
82 罗荣华, 洪炳镕. 基于信息融合的同时定位与地图创建研究[J]. 哈尔滨工业大学学报, 2004, (5): 566- 569.
doi: 10.3321/j.issn:0367-6234.2004.05.002
LUO Ronghua , HONG Bingrong . Research on simultaneous localization and map creation based oninformation fusion[J]. Journal of Harbin Institute of Technology, 2004, (5): 566- 569.
doi: 10.3321/j.issn:0367-6234.2004.05.002
83 崔巍杰. 毫米波和激光雷达数据融合的SLAM算法研究[D]. 成都: 电子科技大学机械工程系, 2019.
CUI Weijie. SLAM algorithm for millimeter wave and LiDAR data fusion[D]. Chengdu: Department of Mechanical, Engineering University of Electronic Science and Technology, 2019.
84 王泽华, 梁冬泰, 梁丹, 等. 基于惯性/磁力传感器与单目视觉融合的slam方法[J]. 机器人, 2018, 40 (6): 933- 941.
WANG Zehua , LIANG Dongtai , LIANG Dan , et al. SLAM method based on inertial/magnetic sensor and monocular vision fusion[J]. The Robot, 2018, 40 (6): 933- 941.
85 HERTZBERG Christoph , WAGNER Rene , FRESE UdO , et al. Integrating generic sensor fusion algorithms with sound state representations through encapsulation of manifolds[J]. Information Fusion, 2011, 14 (1): 57- 77.
86 KO N Y , YOUN Wonkeun , CHOI I H , et al. Features of invariant extended Kalman filter applied to unmanned aerial vehicle navigation[J]. Sensors, 2018, 18 (9): 2855.
doi: 10.3390/s28092855
87 陈梦园, 任玥. 环境感知传感器在车辆智能化中的应用[C]//重庆汽车工程学会2019年论文汇编. 重庆: 重庆汽车工程学会, 2019: 33-38.
CHEN Mengyuan, REN Yue. Application of environmental sensing sensor in vehicle intelligence[C]//Proceedings of Chongqing Automotive Engineering Society. Chongqing: CAES, 2019: 33-38.
88 杨雪梦, 姚敏茹, 曹凯. 移动机器人SLAM关键问题和解决方法综述[J]. 计算机系统应用, 2018, 27 (7): 1- 10.
doi: 10.15888/j.cnki.csa.006451
YANG Xuemeng , YAO Minru , CAO Kai . Review on key problems and solutions for mobile robot SLAM[J]. Application of Computer Systems, 2018, 27 (7): 1- 10.
doi: 10.15888/j.cnki.csa.006451
89 李小玲. SLAM问题中的数据关联方法研究[J]. 计算机产品与流通, 2019, (8): 114.
LI Xiaoling . Research on data association method for SLAM problem[J]. Computer Products & Circulation, 2019, (8): 114.
90 BAR-SHALOM Yaakov , DAUM Fred , HUANG Jim . The probabilistic data association filter[J]. IEEE Control Systems, 2010, 29 (6): 82- 100.
91 BAILEY T, NEBOT E M, ROSENBLATT J K, et al. Data association for mobile robot navigation: a graph theoretic approach[C]//Proceedings of IEEE Int-ernational Conference on Robotics and Automation. San Francisco, USA: IEEE, 2000: 2512-2517.
92 张铁. 移动机器人里程计系统误差的校正方法[J]. 华南理工大学学报(自然科学版), 2014, 42 (9): 7- 11.
ZHANG Tie . Calibration method of mobile robot odometer system error[J]. Journal of South China University of Technology (Natural Science Edition), 2014, 42 (9): 7- 11.
93 余宇, 胡峰. 基于深度学习的视觉SLAM回环检测方法[J]. 计算机工程与设计, 2020, 41 (2): 529- 536.
YU Yu , HU Feng . A Loop detection method for visual SLAM based on deep learning[J]. Computer Engineering and Design, 2020, 41 (2): 529- 536.
94 房立金, 刘博, 万应才. 基于深度学习的动态场景语SLAM[J]. 华中科技大学学报(自然科学版), 2020, 48 (1): 121- 126.
FANG Lijin , LIU Bo , WAN Yingcai . Semantic SLAM for dynamic scenes based on deep learning[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2020, 48 (1): 121- 126.
95 张凯, 阳杰. 深度学习下的视觉SLAM回环检测及其算法[J]. 微处理机, 2021, 42 (1): 43- 46.
ZHANG Kai , YANG Jie . Loop detection and algorithm for visual SLAM based on deep learning[J]. Microprocessor, 2021, 42 (1): 43- 46.
96 张国栋. 基于深度学习的视觉SLAM系统[J]. 电子制作, 2019, (1): 62- 64.
ZHANG Guodong . A visual SLAM system based on deep learning[J]. Electronic Manufacturing, 2019, (1): 62- 64.
97 LI Ruihao , WANG Sen , GU Dongbing . Deep SLAM: a robust monocular SLAM system with unsupervised deeplearning[J]. IEEE Transactions on Industrial Electronics, 2021, 68 (4): 3577- 3587.
doi: 10.1109/TIE.2020.2982096
98 LI Guangqiang , YU Lei , FEI Shumin . A deep-learning real-time visual SLAM system based on multi-task featureextraction network and self-supervised feature points[J]. Measurement, 2021, 168 (4/5): 108403.
99 MEMON A R , WANG Hesheng , HUSSAINAbid . Loop closure detection using supervised and unsupervised deepneural networks for monocular SLAM systems[J]. Robotics and Autonomous Systems, 2020, 126, 103470.
doi: 10.1016/j.robot.2020.103470
100 ZHAO Xinyang , WANG Changhong , ANG M H . Real-time visual-inertial localization using semanticsegmentation towards dynamic environments[J]. IEEE Access, 2020, 8, 155047- 155059.
doi: 10.1109/ACCESS.2020.3018557
101 MANSOUR Mostafa , DAVIDSON Pavel , STEPANOV Oleg . Towards semantic SLAM: 3D position and velocity estimation by fusing image semantic information with camera motion parameters for traffic scene analysis[J]. Remote Sensing, 2021, 13 (3): 17.
102 吴凡, 宗艳桃, 汤霞清. 视觉SLAM的研究现状与展望[J]. 计算机应用研究, 2020, 37 (8): 2248- 2254.
WU Fan, ZONG Yantao, TANG Xiaqing. Application Research of Computers [J]. 2020, 37(8): 2248-2254.
103 KIM Hanme, LEUTENEGGER Stefan, DAVISONA J. Real-time 3D reconstruction and 6-DoF tracking with an event camera[C]//Proceedings of Computer Vision-Eccv 2016. Amsterdam, the Netherlands: ECCV, 2016: 349-364.
104 马艳阳, 叶梓豪, 刘坤华, 等. 基于事件相机的定位与建图算法: 综述[J]. 自动化学报, 2021, 47 (7): 1484- 1494.
MA Yanyang , YE Zihao , LIU Kunhua , et al. Event camera based localization and mapping algorithms: a review[J]. Acta Automatica Sinica, 2021, 47 (7): 1484- 1494.
105 吴建清, 宋修广. 智慧公路关键技术发展综述[J]. 山东大学学报(工学版), 2020, 50 (4): 52- 69.
WU Jianqing , SONG Xiuguang . Review on smart highways critical technology[J]. Journal of Shandong University (Engineering Science), 2020, 50 (4): 52- 69.
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