摘要
视觉SLAM一直是近年来火热的研究方向,其处理对象为视觉图像;深度学习在图像处理中展现出的愈加突出的优势,使二者的广泛结合成为了可能.总结了传统SLAM与基于深度学习的SLAM的特点、性质,重点介绍和总结了深度学习在视觉里程计、回环检测中的研究成果,展望了基于深度学习的视觉SLAM的研究发展方向.
Visual SLAM has been the hot research topic in recent years,which treats visual image as processing objects.Deep learning shows the prominent advantages in image processing,which makes it possible to combine the visual SLAM and deep learning.The characteristics and properties of traditional SLAM and SLAM based on deep learning are summarized.The prominent achievements on visual odometry and loop closure detection incorporated with deep learning are introduced.The future research directions of advanced SLAM based on deep learning are discussed.
作者
李少朋
张涛
LI Shaopeng;ZHANG Tao(Department of Automation,Tsinghua University,Beijing 100084,China;Rocket Force University of Engineering,Xi’an 710025,China)
出处
《空间控制技术与应用》
CSCD
北大核心
2019年第2期1-10,共10页
Aerospace Control and Application
关键词
深度学习
同时定位与建图
视觉里程计
回环检测
deep learning
visual simultaneous localization and mapping (SLAM)
visual odometry
loop closure detection
