面向动态物体场景的视觉SLAM综述

A Survey of Visual SLAM for Scenes with Dynamic Objects

  • 摘要: 针对当前机器人导航、自动驾驶等领域中的热点问题——面向动态物体场景的视觉SLAM(同步定位与地图构建)——进行了综述.根据动态SLAM在定位与建图时对动态物体的不同处理方式,划分了3个研究方向:动态鲁棒性SLAM与静态背景重建、非刚性动态物体跟踪重建、以及移动物体跟踪与重建.对这3个研究方向分别进行了综述,并重点介绍结合了深度学习的动态SLAM方法.最后,展望了动态SLAM的未来发展方向.

     

    Abstract: Visual SLAM (simultaneous localization and mapping) for scenes with dynamic objects is surveyed as a current research hotspot in robot navigation, automatic driving and other fields. Three research directions of dynamic SLAM are classified according to the different ways of handling the dynamic objects in localization and mapping, including dynamic robust SLAM and static background reconstruction, non-rigid dynamic object tracking and reconstruction, and moving object tracking and reconstruction. The three research directions are reviewed respectively, and the dynamic SLAM approaches combined with deep learning are highlighted. Finally, future development directions of dynamic SLAM are envisioned.

     

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