CASIA OpenIR  > 精密感知与控制研究中心  > 精密感知与控制
丁文东1,2; 徐德1,2,3; 刘希龙1,2; 张大朋1,2; 陈天1,2
Source Publication自动化学报
Abstract定位是移动机器人导航的重要组成部分. 在定位问题中, 视觉发挥了越来越重要的作用. 本文首先给出了视觉定位的数学描述, 然后按照数据关联方式的不同介绍了视觉里程计 (Visual odometry, VO) 所使用的较为代表性方法, 讨论了提高视觉里程计鲁棒性的方法. 此外, 本文讨论了语义分析在视觉定位中作用以及如何使用深度学习神经网络进行视觉定位的问题. 最后, 本文简述了视觉定位目前存在的问题和未来的发展方向.
Other Abstract
Localization plays a key role in mobile robot's navigation. Vision becomes more and more important for localization. Firstly, this paper gives the mathematical description of visual localization. Secondly, typical methods of visual odometry (VO) are introduced according to the data association modes. Thirdly, the methods to improve the robustness of visual odometry are discussed. Fourthly, the effect of semantic analysis on visual localization is described. How to use deep neural network in visual localization is also provided. Finally, existing problems and future development trends are presented.
Keyword视觉里程计 视觉定位 位姿估计 导航 移动机器人
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Document Type期刊论文
Corresponding Author徐德
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
丁文东,徐德,刘希龙,等. 移动机器人视觉里程计综述[J]. 自动化学报,2018,44(3):385-400.
APA 丁文东,徐德,刘希龙,张大朋,&陈天.(2018).移动机器人视觉里程计综述.自动化学报,44(3),385-400.
MLA 丁文东,et al."移动机器人视觉里程计综述".自动化学报 44.3(2018):385-400.
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