赵洋, 刘国良, 田国会, 罗勇, 王梓任, 张威, 李军伟. 基于深度学习的视觉SLAM综述[J]. 机器人, 2017, 39(6): 889-896. DOI: 10.13973/j.cnki.robot.2017.0889
引用本文: 赵洋, 刘国良, 田国会, 罗勇, 王梓任, 张威, 李军伟. 基于深度学习的视觉SLAM综述[J]. 机器人, 2017, 39(6): 889-896. DOI: 10.13973/j.cnki.robot.2017.0889
ZHAO Yang, LIU Guoliang, TIAN Guohui, LUO Yong, WANG Ziren, ZHANG Wei, LI Junwei. A Survey of Visual SLAM Based on Deep Learning[J]. ROBOT, 2017, 39(6): 889-896. DOI: 10.13973/j.cnki.robot.2017.0889
Citation: ZHAO Yang, LIU Guoliang, TIAN Guohui, LUO Yong, WANG Ziren, ZHANG Wei, LI Junwei. A Survey of Visual SLAM Based on Deep Learning[J]. ROBOT, 2017, 39(6): 889-896. DOI: 10.13973/j.cnki.robot.2017.0889

基于深度学习的视觉SLAM综述

A Survey of Visual SLAM Based on Deep Learning

  • 摘要: 综述了深度学习技术应用到同步定位与地图创建(SLAM)领域的最新研究进展,重点介绍和总结了深度学习与帧间估计、闭环检测和语义SLAM结合的突出研究成果,并对传统SLAM算法与基于深度学习的SLAM算法做了深入的对比研究.最后,展望了未来基于深度学习的SLAM研究发展方向.

     

    Abstract: Latest research progresses of deep learning techniques applied to SLAM (simultaneous localization and mapping) are summarized. In addition, the prominent achievements on inter-frame motion estimation, loop closure detection and semantic SLAM incorporated with deep learning are introduced. Furthermore, the deep learning based SLAM is compared with the traditional ones in detail. Finally, the future research directions of advanced SLAM based on deep learning are discussed.

     

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