| 基于深度学习的视觉SLAM综述 |
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| 引用本文： | 刘瑞军,王向上,张晨,章博华.基于深度学习的视觉SLAM综述[J].系统仿真学报,2020,32(7):1244-1256. |
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| 作者姓名： | 刘瑞军 王向上 张晨 章博华 |
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| 作者单位： | 北京工商大学计算机与信息工程学院食品安全大数据技术北京市重点实验室,北京 100048 |
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| 摘 要： | 随着计算机视觉和机器人技术的发展,视觉同时定位与地图创建已成为无人系统领域的研究焦点,深度学习在图像处理方面展现出的强大优势,为二者的广泛结合创造了机会。总结了深度学习与视觉里程计、闭环检测和语义同时定位与地图创建结合的突出研究成果,对传统算法与基于深度学习的方法做了对比,展望了基于深度学习的视觉同时定位与地图创建发展方向。
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| 关 键 词： | 视觉同步定位与地图创建 深度学习 视觉里程计 闭环检测 语义同步定位与地图创建 |
| 收稿时间： | 2019-08-30 |
A Survey on Visual SLAM based on Deep Learning |
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| Liu Ruijun,Wang Xiangshang,Zhang Chen,Zhang Bohua.A Survey on Visual SLAM based on Deep Learning[J].Journal of System Simulation,2020,32(7):1244-1256. |
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| Authors: | Liu Ruijun Wang Xiangshang Zhang Chen Zhang Bohua |
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| Institution: | Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China |
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| Abstract: | Following the development of computer vision and robotics, visual Simultaneous Localization and Mapping becomes a research focus in the field of unmanned systems. The powerful advantages of deep learning in the image processing offer a huge opportunity to the wide combination of the two fields. The outstanding research achievements of deep learning combined with visual odometry, loop closure detection and semantic Simultaneous Localization and Mapping are summarized. A comparison between the traditional algorithm and method based on deep learning is carried out. The development direction of visual Simultaneous Localization and Mapping based on deep learning is forecasted. |
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| Keywords: | deep learning Visual Simultaneous Localization and Mapping visual odometry loop closure detection semantic Simultaneous Localization and Mapping |
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