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.
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.
出处
《机器人》
EI
CSCD
北大核心
2017年第6期889-896,共8页
Robot
基金
国家自然科学基金(61603213)
中国博士后科学基金(2016M590635)
山东省优秀中青年科学家科研奖励基金(BS2014DX010)
山东大学人才引进与培养类专项基金(2015TB009)
山东省泰山学者工程
关键词
深度学习
视觉SLAM
帧间估计
视觉里程计
闭环检测
语义SLAM
deep learning
visual SLAM(simultaneous localization and mapping)
inter-frame motion estimation
visual odometry
loop closure detection
semantic SLAM
