Page 128 - 《武汉大学学报(信息科学版)》2025年第10期
P. 128
第 50 卷第 10 期 张晨阳等:一种自适应点线特征和 IMU 耦合的视觉 SLAM 方法 2063
Estimator [J]. IEEE Transactions on Robotics, Merge of Point and Line Features[J]. Acta Aero‑
2018, 34(4): 1004-1020. nautica et Astronautica Sinica, 2022, 43(3) :
[22] QIN T, CAO S Z, PAN J, et al. A General Opti‑ 363-377.
mization-Based Framework for Global Pose Estima‑ [30] 应文健, 潘林豪, 佘博, 等 . 融合点线特征的双目
tion with Multiple Sensors[EB/OL]. (2019-1-11) 视 觉 -惯 导 SLAM 算 法[J]. 海 军 工 程 大 学 学 报 ,
[2022-7-10]. https://arxiv. org/pdf/1901. 03642v1. 2021, 33(6): 106-112.
[23] 龚赵慧, 张霄力, 彭侠夫, 等 . 基于视觉惯性融合 YING Wenjian, PAN Linhao, SHE Bo, et al. Ste‑
的 半 直 接 单 目 视 觉 里 程 计[J]. 机 器 人 , 2020, 42 reo Visual-Inertial SLAM Algorithm Based on Point
(5): 595-605. and Line Features[J]. Journal of Naval University
GONG Zhaohui, ZHANG Xiaoli, PENG Xiafu, et of Engineering, 2021, 33(6): 106-112.
al. Semi-Direct Monocular Visual Odometry Based [31] 危双丰, 师现杰, 刘振彬, 等 . 点线联合的优化视
on Visual-Inertial Fusion[J]. Robot, 2020, 42(5): 觉惯性里程计[J]. 测绘科学,2021, 46(4): 20-27.
595-605. WEI Shuangfeng, SHI Xianjie, LIU Zhenbin, et al.
[24] 许智宾 . 基于双目视觉与惯导融合的移动机器人室 Point-and-Line Joint Optimization Visual Inertial
内定位技术研究[D]. 郑州:郑州大学, 2021. Odometer[J]. Science of Surveying and Mapping,
XU Zhibin. Research on Indoor Positioning Technolo‑ 2021, 46(4): 20-27.
gy of Mobile Robot Based on Fusion of Binocular Vi‑ [32] GIOI R G, JAKUBOWICZ J, MOREL J M, et al.
sion and Inertial Navigation[D]. Zhengzhou:Zheng‑ LSD: A Fast Line Segment Detector with a False
zhou University, 2021. Detection Control[J]. IEEE Transactions on Pat‑
[25] 张福斌, 张炳烁, 杨玉帅 . 基于单目/IMU/里程计 tern Analysis and Machine Intelligence, 2010, 32
融合的 SLAM 算法[J]. 兵工学报, 2022, 43(11): (4): 722-732.
2810-2818. [33] 贾迪, 朱宁丹, 杨宁华, 等 . 图像匹配方法研究综
ZHANG Fubin,ZHANG Bingshuo, YANG Yushuai. 述[J]. 中 国 图 象 图 形 学 报 , 2019, 24(5): 677-
SLAM Algorithm Based on Monocular/IMU/Odome‑ 699.
ter Fusion[J]. Acta Armamentarii, 2022, 43(11): JIA Di, ZHU Ningdan,YANG Ninghua, et al. Image
2810-2818. Matching Methods[J]. Journal of Image and
[26] HE Y J,ZHAO J,GUO Y,et al. PL-VIO: Tightly- Graphics, 2019, 24(5): 677-699.
Coupled Monocular Visual-Inertial Odometry Using [34] LU X H, YAOY J, LI H A, et al. 2-Line Exhaus‑
Point and Line Features[J]. Sensors, 2018, 18(4): tive Searching for Real-Time Vanishing Point Esti‑
1159. mation in Manhattan World[C]//IEEE Winter Con‑
[27] FU Q, WANG J L, YU H S, et al. PL-VINS: ference on Applications of Computer Vision
Real-Time Monocular Visual-Inertial SLAM with (WACV), Santa Rosa, CA, USA, 2017.
Point and Line Features[EB/OL]. (2020-9-16) [35] ZHANG L L, KOCH R. An Efficient and Robust
[2022-7-15]. https://arxiv. org/abs/2009. 07462. Line Segment Matching Approach Based on LBD
[28] LEE J, PARK S Y. PLF-VINS: Real-Time Mono‑ Descriptor and Pairwise Geometric Consistency[J].
cular Visual-Inertial SLAM with Point-Line Fusion Journal of Visual Communication and Image Repre‑
and Parallel-Line Fusion[J]. IEEE Robotics and sentation, 2013, 24(7): 794-805.
Automation Letters, 2021, 6(4): 7033-7040. [36] 高翔, 张涛, 刘毅, 等 . 视觉 SLAM 十四讲: 从理
[29] 赵良玉, 金瑞, 朱叶青, 等 . 基于点线特征融合的 论到实践[M]. 北京: 电子工业出版社, 2017.
双 目 惯 性 SLAM 算 法[J]. 航 空 学 报 , 2022, 43 GAO Xiang, ZHANG Tao, LIU Yi, et al. Four‑
(3): 363-377. teen Lectures on Visual SLAM: From Theory to
ZHAO Liangyu, JIN Rui, ZHU Yeqing, et al. Ste‑ Practice[M]. Beijing: Publishing House of Electronics
reo Visual-Inertial SLAM Algorithm Based on Industry, 2017.

