Journal of Shandong University(Engineering Science) ›› 2025, Vol. 55 ›› Issue (3): 1-15.doi: 10.6040/j.issn.1672-3961.0.2024.180
• Transportation Engineering—Special Issue for Intelligent Transportation •
LÜ Bin1, LIU Miao1, WU Jianqing2*, ZHANG Ziyi2, CHEN Qixiang1
CLC Number:
| [1] 李熹明. 智能交通运输的未来发展趋势与挑战[J]. 运输经理世界, 2024(7): 49-51. LI Ximing. Future development trends and challenges of intelligent transportation[J]. Transport Business China, 2024(7): 49-51. [2] 吴建清, 宋修广. 同步定位与建图技术发展综述[J]. 山东大学学报(工学版), 2021, 51(5): 16-31. WU Jianqing, SONG Xiuguang. Review on development of simultaneous localization and mapping technology[J]. Journal of Shandong University(Engineering Science), 2021, 51(5): 16-31. [3] 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. Long-term autonomous environment adaptation of mobile robots: state-of-the-art methods and prospects[J]. Acta Automatica Sinica, 2020, 46(2): 205-221. [4] YU S E, FU C Y, GOSTAR A K, et al. A review on map-merging methods for typical map types in multiple-ground-robot SLAM solutions[J]. Sensors, 2020, 20(23): 6988. [5] 刘鑫, 王忠, 秦明星. 多机器人协同SLAM技术研究进展[J]. 计算机工程, 2022, 48(5): 1-10. LIU Xin, WANG Zhong, QIN Mingxing. Research progress of multi-robot collaborative SLAM technology[J]. Computer Engineering, 2022, 48(5): 1-10. [6] 李纪鑫, 吴宗卓, 赫磊, 等. 多机器人协同的SLAM算法研究[J]. 自动化与仪器仪表, 2023(9): 205-209. LI Jixin, WU Zongzhuo, HE Lei, et al. SLAM algorithm for multi-robot collaboration[J]. Automation & Instru-mentation, 2023(9): 205-209. [7] 阴贺生, 裴硕, 徐磊,等. 多机器人视觉同时定位与建图技术研究综述[J]. 机械工程学报, 2022, 58(11): 11-36. YIN Hesheng, PEI Shuo, XU Lei, et al. Review of research on multi-robot visual simultaneous localization and mapping[J]. Journal of Mechanical Engineering, 2022, 58(11): 11-36. [8] ISHIOKA K.HIRAKI K, ANZAI Y. Cooperative map generation by heterogenous autonomous mobile robots[C] //IJCAI'93 Workshop on Dynamically Interacting Robots. Chambery, France: [s.n.] , 1993: 57-67. [9] WILLIAMS S B, DISSANAYAKE G, DURRANTWHYTE H. Towards multi-vehicle simultaneous localisation and mapping[C] //Proceedings 2002 IEEE International Conference on Robotics and Automation. Washington, D.C., USA: IEEE, 2002: 2743-2748. [10] KO J, STEWART B, FOX D, et al. A practical, decision-theoretic approach to multi-robot mapping and exploration[C] //Proceedings 2003 IEEE/RSJ Inter-national Conference on Intelligent Robots and Systems(IROS 2003). Las Vegas, USA: IEEE, 2003: 3232- 3238. [11] KONOLIGE K, FOX D, LIMKETKAI B, et al. Map merging for distributed robot navigation[C] //Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2003). Las Vegas, USA: IEEE, 2003: 212-217. [12] LYNCH M P, SAALFELD A J. Conflation: automated map compilation:a video game approach[C] //7th International Symposium on Computer-Assisted Cartogra-phy(Auto Carto 7). Washington, D.C., USA: [s.n.] , 1985: 343-352. [13] DENG S S, TONG X H. A new least squares adjustment method for map conflation[C] //Geoinformatics 2006: Geospatial Information Science. Wuhan, China: SPIE, 2006: 400-411. [14] FILIN S, DOYTSHER Y. A linear mapping approach to map conflation: matching of polylines[J]. Surveying and Land Information Systems, 1999, 59(2): 107-114. [15] FILIN S, DOYTSHER Y. A linear conflation approach for the integration of photogrammetric information and GIS data[J]. International Archives of Photogrammetry and Remote Sensing, 2000, 33: 282-288. [16] ZHANG Q. Research on feature matching and conflation of geographic databases [D]. Wuhan: University of Wuhan, 2002. [17] RONE W, BEN-TZVI P. Mapping, localization and motion planning in mobile multi-robotic systems[J]. Robotica, 2013, 31(1): 1-23. [18] ELFES A. Using occupancy grids for mobile robot perception and navigation[J]. Computer, 1989, 22(6): 46-57. [19] RYDE J, HU H S. 3D mapping with multi-resolution occupied voxel lists[J]. Autonomous Robots, 2010, 28(2): 169-185. [20] 刘朋, 任工昌. 特征地图的室内机器人路径规划融合算法[J]. 计算机科学与探索, 2023, 17(11): 2755-2766. LIU Peng, REN Gongchang. Path planning fusion algorithm for indoor robot based on feature map[J]. Journal of Frontiers of Computer Science and Techno-logy, 2023, 17(11): 2755-2766. [21] 王娜, 马昕. 基于细化算法的移动机器人拓扑地图创建[J]. 计算机技术与发展, 2009, 19(10): 11-13. WANG Na, MA Xin. Mobile robot topological map building based on thinning algorithm[J]. Computer Technology and Development, 2009, 19(10): 11-13. [22] KOLHATKAR C, WAGLE K. Review of SLAM algo-rithms for indoor mobile robot with LiDAR and RGB-D camera technology[C] // Innovations in Electrical and Electronic Engineering. Singapore: Springer Singapore, 2021: 397-409. [23] 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. CUI Yang. Research on synchronous positioning and map construction algorithm of intelligent mobile robot[J]. Electronics World, 2013(23): 113-114. [24] ANDERSONE I. Heterogeneous map merging:state of the art[J]. Robotics, 2019, 8(3): 74. [25] WU J Q, ZHUANG X C, TIAN Y, et al. Real-time point cloud clustering algorithm based on roadside LiDAR[J]. IEEE Sensors Journal, 2024, 24(7): 10608-10619. [26] WU J Q, XU H, ZHENG J Y. Automatic background filtering and lane identification with roadside LiDAR data[C] //2017 IEEE 20th International Conference on Intelligent Transportation Systems(ITSC). Yokohama, Japan: IEEE, 2017: 1-6. [27] LÜ B, XU H, WU J Q, et al. Revolution and rotation-based method for roadside LiDAR data integration[J]. Optics & Laser Technology, 2019, 119: 105571. [28] WU J Q, XU H, LIU W. Points registration for roadside LiDAR sensors[J]. Transportation Research Record, 2019, 2673(9): 627-639. [29] YUE R, XU H, WU J Q, et al. Data registration with ground points for roadside LiDAR sensors[J]. Remote Sensing, 2019, 11(11): 1354. [30] SAEEDI S, TRENTINI M, SETO M, et al. Multiple-robot simultaneous localization and mapping: a review[J]. Journal of Field Robotics, 2016, 33(1): 3-46. [31] MOHANARAJAH G, USENKO V, SINGH M, et al. Cloud-based collaborative 3D mapping in real-time with low-cost robots[J]. IEEE Transactions on Automation Science and Engineering, 2015, 12(2): 423-431. [32] MARCOTTE R J, WANG X P, MEHTA D, et al. Optimizing multi-robot communication under bandwidth constraints[J]. Autonomous Robots, 2020, 44(1): 43-55. [33] MARJOVI A, CHOOBDAR S, MARQUES L. Robotic clusters: multi-robot systems as computer clusters A topological map merging demonstration[J]. Robotics and Autonomous Systems, 2012, 60(9): 1191-1204. [34] JESSUP J, GIVIGI S N, BEAULIEU A. Robust and efficient multirobot 3D mapping merging with octree-based occupancy grids[J]. IEEE Systems Journal, 2015, 11(3): 1723-1732. [35] HUSAIN A, JONES H, KANNAN B, et al. Mapping planetary caves with an autonomous, heterogeneous robot team[C] //2013 IEEE Aerospace Conference. Big Sky, USA: IEEE, 2013:1-13. [36] FERR(~overA)O V T, VINHAL C D N, DA CRUZ G. An occupancy grid map merging algorithm invariant to scale, rotation and translation[C] //2017 Brazilian Conference on Intelligent Systems(BRACIS). Uber-landia, Brazil: IEEE, 2017: 246-251. [37] HOWARD A. Multi-robot simultaneous localization and mapping using particle filters[J]. The International Journal of Robotics Research, 2006, 25(12): 1243-1256. [38] CHEN B F, LI S Y, ZHAO H W, et al. Map merging with suppositional box for multi-robot indoor mapping[J]. Electronics, 2021, 10(7): 815. [39] SAEEDI S, TRENTINI M, LI H. A hybrid approach for multiple-robot SLAM with particle filtering[C] //2015 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS). Hamburg, Germany: IEEE, 2015: 3421-3426. [40] 任健铭. 基于三维激光点云的室内机器人即时定位与建图算法研究[D]. 哈尔滨: 哈尔滨工业大学, 2019. REN Jianming. Simultaneous localization and mapping algorithms for indoor robots based on three-dimensional laser point cloud[D]. Harbin: Harbin Institute of Technology, 2019. [41] SMITH R, SELF M, CHEESEMAN P. Autonomous robot vehicles[M]. New York: Springer, 1990: 167-193. [42] PEI F J, ZHU M J, WU X P. A decorrelated distributed EKF-SLAM system for the autonomous navigation of mobile robots[J]. Journal of Intelligent & Robotic Systems, 2020, 98(3): 819-829. [43] 周振, 王冬青, 许柏杨,等. 基于改进多新息理论的EKF-SLAM算法[J]. 自动化与仪器仪表, 2020(6): 21-25. ZHOU Zhen, WANG Dongqing, XU Boyang, et al. EKF-SLAM algorithm based on improved multi-innovation theory[J]. Automation & Instrumentation, 2020(6): 21-25. [44] 蔡艳, 杨光永, 黄训爱,等. 多策略鲸鱼算法优化粒子滤波的SLAM精度研究[J]. 重庆理工大学学报(自然科学), 2023, 37(6): 136-145. CAI Yan, YANG Guangyong, HUANG Xun'ai, et al. Research on SLAM accuracy of paricle filter optimized by multi-strategy whale algorithm[J]. Journal of Chongqing University of Technology(Natural Science), 2023, 37(6): 136-145. [45] 曹洁, 荆银银, 王进花. 基于改进的萤火虫算法优化粒子滤波方法[J]. 兰州理工大学学报, 2018, 44(4): 84-89. CAO Jie, JING Yinyin, WANG Jinhua. Optimized particle filter algorithm based on improved firefly algorithm[J]. Journal of Lanzhou University of Technology, 2018, 44(4): 84-89. [46] LU F, MILIOS E. Globally consistent range scan alignment for environment mapping[J]. Autonomous Robots, 1997, 4(4): 333-349. [47] OLSON E B. Robust and efficient robotic mapping[D]. Cambridge: Massachusetts Institute of Technology, 2008. [48] FRESE U. Treemap: an O(log n)algorithm for indoor simultaneous localization and mapping[J]. Autonomous Robots, 2006, 21(2): 103-122. [49] GRISETTI G, STACHNISS C, GRZONKA S, et al. A tree parameterization for efficiently computing maximum likelihood maps using gradient descent[C] //Robotics: Science and Systems. Atlanta, USA: [s.n.] , 2007: 65-72. [50] KAESS M, RANGANATHAN A, DELLAERT F. iSAM:incremental smoothing and mapping[J]. IEEE Transactions on Robotics, 2008, 24(6): 1365-1378. [51] 颜普, 曹昊宇, 雷为好. 基于改进图优化的激光SLAM算法[J]. 安徽大学学报(自然科学版), 2023, 47(4): 35-41. YAN Pu, CAO Haoyu, LEI Weihao. Laser SLAM algorithm based on improved graph optimization[J]. Journal of Anhui University(Natural Science Edition), 2023, 47(4): 35-41. [52] SCHUSTER M J, BRAND C, HIRSCHMÜLLER H, et al. Multi-robot 6D graph SLAM connecting decoupled local reference filters[C] //2015 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS). Hamburg, Germany: IEEE, 2015: 5093-5100. [53] ERINC G, BALAGUER B, CARPIN S. Heterogeneous map merging using WiFi signals[C] //2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. Tokyo, Japan: IEEE, 2013: 5258-5264. [54] LEE H C, LEE S H, CHOI M H, et al. Probabilistic map merging for multi-robot RBPF-SLAM with unknown initial poses [J]. Robotica, 2012, 30(2): 205-220. [55] BURGARD W, MOORS M, FOX D, et al. Collaborative multi-robot exploration[C] // IEEE International Confer-ence on Robotics and Automation(ICRA). San Francisco, USA: IEEE, 2000: 476-481. [56] 郝奇, 陈智君, 郑亮,等. 基于概率匹配的栅格地图拼接算法[J]. 组合机床与自动化加工技术, 2022(5): 83-87. HAO Qi, CHEN Zhijun, ZHENG Liang, et al. Mosaic algorithm of grid map based on probability matching[J]. Modular Machine Tool & Automatic Manufacturing Technique, 2022(5): 83-87. [57] CARPIN S, BIRK A, JUCIKAS V. On map merging[J]. Robotics and Autonomous Systems, 2005, 53(1): 1-14. [58] BIRK A, CARPIN S. Merging occupancy grid maps from multiple robots[J]. Proceedings of the IEEE, 2006, 94(7): 1384-1397. [59] LI H, NASHASHIBI F. A new method for occupancy grid maps merging: application to multi-vehicle cooperative local mapping and moving object detection in outdoor environment[C] //2012 12th International Conference on Control Automation Robotics & Vision(ICARCV). Guangzhou, China: IEEE, 2012: 632-637. [60] LI H, NASHASHIBI F. Multi-vehicle cooperative localization using indirect vehicle-to-vehicle relative pose estimation[C] //2012 IEEE International Conference on Vehicular Electronics and Safety(ICVES 2012). Istanbul, Turkey: IEEE, 2012: 267-272. [61] MA L, ZHU J H, ZHU L, et al. Merging grid maps of different resolutions by scaling registration[J]. Robotica, 2016, 34(11): 2516-2531. [62] 黄小杭, 曾碧, 刘建圻, 等. 融合图特征的多机器人栅格地图拼接方法[J]. 计算机工程与应用, 2022, 58(14): 299-305. HUANG Xiaohang, ZENG Bi, LIU Jianqi, et al. Multi-robot grid map stitching method combining graph features[J]. Computer Engineering and Applications, 2022, 58(14): 299-305. [63] 唐宏伟, 孙炜, 杨凯, 等. 基于SURF特征的多机器人栅格地图拼接方法[J]. 电子测量与仪器学报, 2017, 31(6): 859-868. TANG Hongwei, SUN Wei, YANG Kai, et al. Grid map merging approach of multi-robot based on SURF feature[J]. Journal of Electronic Measurement and Instrumentation, 2017, 31(6): 859-868. [64] 李雅梅, 苏龙. 一种基于局部特征的栅格地图拼接方法[J]. 计算机应用与软件, 2020, 37(1): 110-115. LI Yamei, SU Long. A grid map merging approach based on local feature[J]. Computer Applications and Software, 2020, 37(1): 110-115. [65] 张子毅, 孙焘, 王琦, 等. 基于坐标转换和ICP算法的水利点云配准方法[J]. 山东大学学报(工学版), 2024, 54(5): 155-162. ZHANG Ziyi, SUN Tao, WANG Qi, et al. Point cloud registration method of water conservancy based on coordinate transformation and ICP algorithm[J]. Journal of Shandong University(Engineering Science), 2024, 54(5): 155-162. [66] 纪华, 吴元昊, 孙宏海, 等. 结合全局信息的SIFT特征匹配算法[J]. 光学精密工程, 2009, 17(2): 439-444. JI Hua, WU Yuanhao, SUN Honghai, et al. SIFT feature matching algorithm with global information[J]. Optics and Precision Engineering, 2009, 17(2): 439-444. [67] 李发帅, 肖建华, 王诗云, 等. 基于分块SIFT的特征提取与无人机影像拼接方法[J]. 城市勘测, 2020(5): 5-9. LI Fashuai, XIAO Jianhua, WANG Shiyun, et al. A block-based SIFT feature extraction algorithm and UAV image stitching method[J]. Urban Geotechnical Investigation & Surveying, 2020(5): 5-9. [68] 王飞越. 基于SURF特征提取的图像配准算法研究[D]. 哈尔滨: 哈尔滨理工大学, 2018. WANG Feiyue. Study on the image registration algorithm based on SURF feature extraction[D]. Harbin: Harbin University of Science and Technology, 2018. [69] 杨弘凡, 李航, 陈凯阳, 等. 基于改进ORB算法的图像特征点提取与匹配方法[J]. 图学学报, 2020, 41(4): 548-555. YANG Hongfan, LI Hang, CHEN Kaiyang, et al. Image feature points extraction and matching method based on improved ORB algorithm[J]. Journal of Graphics, 2020, 41(4): 548-555. [70] 秦志钢. 改进的ORB特征提取及描述算法[J]. 集成电路应用, 2022, 39(2): 132-133. QIN Zhigang. Improved ORB feature extraction and description algorithm[J]. Applications of IC, 2022, 39(2): 132-133. [71] SUN S Q, XU B L, SUN Y D, et al. Sparse pointcloud map fusion of multi-robot system[C] //2018 Inter-national Conference on Control, Automation and Information Sciences(ICCAIS). Hangzhou, China: IEEE, 2018: 270-274. [72] NGUYEN V, GÄCHTER S, MARTINELLI A, et al. A comparison of line extraction algorithms using 2D range data for indoor mobile robotics[J]. Autonomous Robots, 2007, 23(2): 97-111. [73] 龚雪晶, 慈林林, 姚康泽. 分裂合并算法的优化及并行化方案[J]. 北京理工大学学报, 2007,27(9): 801-806. GONG Xuejing, CI Linlin, YAO Kangze. An effective merge criterion and two parallel strategies for split and merge algorithm[J]. Transactions of Beijing Institute of Technology, 2007, 27(9): 801-806. [74] 张鹏, 武刚, 任柯光. 增量式块主成分分析的焊缝图像特征提取算法[J]. 光电子·激光, 2022, 33(8): 851-857. ZHANG Peng, WU Gang, REN Keguang. Feature extraction algorithm of weld image based on incremental block principal component analysis[J]. Journal of Optoelectronics·Laser, 2022, 33(8): 851-857. [75] 许勇, 刘树惠, 吴锐. 基于概率Hough线段检测算法的天花板影像边界提取[J]. 计算机与数字工程, 2023, 51(4): 939-942. XU Yong, LIU Shuhui, WU Rui. Ceiling image boundary extraction based on probabilistic Hough line segment detection algorithm[J]. Computer & Digital Engineering, 2023, 51(4): 939-942. [76] 邵政毅. 基于线性回归的特征提取算法研究[D]. 无锡:江南大学, 2021. SHAO Zhengyi. Feature extraction algorithm based on linear regression[D]. Wuxi: Jiangnan University, 2021. [77] 王植, 李慧盈, 吴立新,等. 基于RANSAC模型的机载LiDAR数据中建筑轮廓提取算法[J]. 东北大学学报(自然科学版), 2012, 33(2): 271-275. WANG Zhi, LI Huiying, WU Lixin, et al. Building outline extraction from airborne LiDAR data based on RANSAC model[J]. Journal of Northeastern University(Natural Science), 2012, 33(2): 271-275. [78] 张宗军, 杨风暴. 基于改进最大期望聚类的遥感影像道路提取算法[J]. 激光与光电子学进展, 2020, 57(6):061005. ZHANG Zongjun, YANG Fengbao. Road extraction algorithm for remote sensing images based on improved expectation-maximization clustering[J]. Laser & Optoelectronics Progress, 2020, 57(6): 061005. [79] ELSEBERG J, CREED R T, LAKAEMPER R. A line segment based system for 2D global mapping[C] //2010 IEEE International Conference on Robotics and Aut-omation. Anchorage, USA: IEEE, 2010: 3924-3931. [80] SARKAR B, PAL P K, SARKAR D. Building maps of indoor environments by merging line segments extracted from registered laser range scans[J]. Robotics and Autonomous Systems, 2014, 62(4): 603-615. [81] AMIGONI F, LI A Q. Comparing methods for merging redundant line segments in maps[J]. Robotics and Autonomous Systems, 2018, 99: 135-147. [82] AMIGONI F, VAILATI M. A method for reducing redundant line segments in maps[C] //Fourth European Conference on Mobile Robots(ECMR). Dubrovnik, Croatia: [s.n.] , 2009: 61-66. [83] GAO H M, ZHANG X B, LI C P, et al. Directional endpoint-based enhanced EKF-SLAM for indoor mobile robots[C] //2019 IEEE/ASME International Conference on Advanced Intelligent Mechatronics(AIM). Hong Kong, China: IEEE, 2019: 978-983. [84] GOMEZ-OJEDA R, MORENO F A, ZUÑIGA-NOËL D, et al. PL-SLAM: a stereo SLAM system through the combination of points and line segments[J]. IEEE Transactions on Robotics, 2019, 35(3): 734-746. [85] LIU J C, MENG Z Y. Visual SLAM with drift-free rotation estimation in Manhattan world[J]. IEEE Robotics and Automation Letters, 2020, 5(4): 6512-6519. [86] LI F Y, FU C Y, SUN D Y, et al. Reducing redundancy in maps without lowering accuracy: a geometric feature fusion approach for simultaneous localization and mapping[J]. ISPRS International Journal of Geo-Information, 2023, 12(6): 235. [87] AMIGONI F, GASPARINI S, GINI M. Merging partial maps without using odometry[C] //3rd International Workshop on Multi-Robot Systems. Washington, D.C., USA: Springer, 2005: 133-144. [88] LI F Y, FU C Y, GOSTAR A K, et al. Advanced mapping using planar features segmented from 3D point clouds[C] //2019 International Conference on Control, Automation and Information Sciences(ICCAIS). Chengdu, China: IEEE, 2019: 1-6. [89] FISCHLER M A, BOLLES R C. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography[J]. Communications of the ACM, 1981, 24(6):381-395 [90] BAB-HADIASHAR A, SUTER D. Robust segmentation of visual data using ranked unbiased scale estimate[J]. Robotica, 1999, 17(6): 649-660. [91] SUN Q X, YUAN J, ZHANG X B, et al. Plane-edge-SLAM: seamless fusion of planes and edges for SLAM in indoor environments[J]. IEEE Transactions on Automation Science and Engineering, 2021, 18(4): 2061-2075. [92] GOSTAR A K, FU C Y, CHUAH W, et al. State transition for statistical SLAM using planar features in 3D point clouds[J]. Sensors, 2019, 19(7): 1614. [93] PAN L, WANG P F, CAO J W, et al. Dense RGB-D SLAM with planes detection and mapping[C] //IECON 2019-45th Annual Conference of the IEEE Industrial Electronics Society. Lisbon, Portugal: IEEE, 2019: 5192-5197. [94] HUANG W H, BEEVERS K R. Topological map merging[J]. The International Journal of Robotics Research, 2005, 24(8): 601-613. [95] DUPAS A, DAMIAND G. Comparison of local and global region merging in the topological map[C] //12th International Workshop on Combinatorial Image Analysis. Buffalo, USA: [s.n.] , 2008: 420-431. [96] 贾松敏, 李雨晨, 王可, 等. RTM框架下基于分层拓扑结构的多机器人系统地图拼接[J]. 机器人, 2013, 35(3): 292-298. JIA Songmin, LI Yuchen, WANG Ke, et al. Map merging for multi-robot systems based on hierarchical topology structure under RTM framework[J]. Robot, 2013, 35(3): 292-298. [97] ANDERSONE I. Distributed framework for reversible merging of heterogeneous robot maps[C] //13th International Conference on Agents and Artificial Intelligence(ICAART 2021). [S.l.] : [s.n.] , 2021: 422-430. [98] ADLURU N, LATECKI L J, SOBEL M, et al. Merging maps of multiple robots[C] //2008 19th International Conference on Pattern Recognition. Tampa, USA: IEEE, 2008: 1-4. [99] ALNOUNOU Y, PAULIK M J, KRISHNAN M, et al. Occupancy grid map merging using feature maps[C] //IASTED International Conference on Robotics and Applications. Cambridge, USA: [s.n.] , 2010: 469-475. [100] ANDERSONE I. Probabilistic mapping with ultrasonic distance sensors[J]. Procedia Computer Science, 2017, 104: 362-368. [101] JOO K, LEE T K, BAEK S, et al. Generating topological map from occupancy grid-map using virtual door detection[C] //IEEE Congress on Evolutionary Computation. Barcelona, Spain: IEEE, 2010: 1-6. [102] FABRIZI E, SAFFIOTTI A. Extracting topology-based maps from gridmaps[C] //2000 IEEE International Conference on Robotics and Automation. San Francisco, USA: IEEE, 2000: 2972-2978. [103] HOWARD A, SIDDIQI S, SUKHATME A G S. Field and service robotics[M]. Berlin: Springer, 2006: 145-153. [104] BALAGUER B, ERINC G, CARPIN S. Combining classification and regression for WiFi localization of heterogeneous robot teams in unknown environments[C] //2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. Vilamoura-Algarve, Portugal: IEEE, 2012: 3496-3503. [105] MIELLE M, MAGNUSSON M, LILIENTHAL A J. Using sketch-maps for robot navigation: interpretation and matching[C] //2016 IEEE International Symposium on Safety, Security, and Rescue Robotics(SSRR). Lausanne, Switzerland: IEEE, 2016: 252-257. [106] JIANG Z T, ZHU J H, JIN C C, et al. Simultaneously merging multi-robot grid maps at different resolutions[J]. Multimedia Tools and Applications, 2020, 79(21): 14553-14572. [107] BAUDOUIN L, MEZOUAR Y, AIT-AIDER O, et al. Multi-modal sensors path merging[C] //13th International Conference on Intelligent Autonomous Systems(IAS). Berlin, Germany: Springer, 2016: 191-201. [108] YUE Y F, YANG C L, WANG Y Z, et al. Multi-robot map fusion framework using heterogeneous sensors[C] //2019 IEEE International Conference on Cybernetics and Intelligent Systems(CIS)and IEEE Conference on Robotics, Automation and Mechatronics(RAM). Bangkok, Thailand: IEEE, 2019: 536-541. [109] 吴建清, 王其峰, 厉周缘, 等. 互通式立交风险冲突识别与预警综述[J]. 山东大学学报(工学版), 2022, 52(6): 1-13. WU Jianqing, WANG Qifeng, LI Zhouyuan, et al. Review of risk conflict identification and early warning for interchange[J]. Journal of Shandong University(Engineering Science), 2022, 52(6): 1-13. |
| [1] | Jianqing WU,Xiuguang SONG. Review on development of simultaneous localization and mapping technology [J]. Journal of Shandong University(Engineering Science), 2021, 51(5): 16-31. |
| [2] | Qijie ZOU,Haoyu LI,Rubo ZHANG,Tengda PEI,Yan LIU. Survey of human-robot interaction control for autonomous driving [J]. Journal of Shandong University(Engineering Science), 2019, 49(2): 23-33. |
| [3] | Fengyu ZHOU, Fang WAN, Jiancheng JIAO, Junjian BIAN. Design for autonomous charging system of family companion robot [J]. Journal of Shandong University(Engineering Science), 2019, 49(1): 55-65. |
| [4] | ZHANG Li, ZHAO Chun-xia*. A new FastSLAM algorithm based on iterated EKF [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2012, 42(4): 41-47. |
|
||
