论文标题
基于视觉的本地化方法在受GPS约束条件下
Vision-based localization methods under GPS-denied conditions
论文作者
论文摘要
本文回顾了基于视力的本地化方法在GPS有限的环境中，并将主流方法分为相对视觉定位（RVL）和绝对视觉定位（AVL）。对于RVL，我们讨论了光流在基于特征提取的视觉进程（VO）溶液中的广泛应用，并引入了先进的光流估计方法。对于AVL，我们回顾了视觉同时定位和映射（VSLAM）技术的最新进展，从基于优化的方法到基于扩展的Kalman滤波器（EKF）方法。我们还介绍了离线地图注册和车道视觉检测方案的应用，以实现绝对的视觉定位。本文比较了主流方法在视觉定位中的性能和应用，并为将来的研究提供了建议。
This paper reviews vision-based localization methods in GPS-denied environments and classifies the mainstream methods into Relative Vision Localization (RVL) and Absolute Vision Localization (AVL). For RVL, we discuss the broad application of optical flow in feature extraction-based Visual Odometry (VO) solutions and introduce advanced optical flow estimation methods. For AVL, we review recent advances in Visual Simultaneous Localization and Mapping (VSLAM) techniques, from optimization-based methods to Extended Kalman Filter (EKF) based methods. We also introduce the application of offline map registration and lane vision detection schemes to achieve Absolute Visual Localization. This paper compares the performance and applications of mainstream methods for visual localization and provides suggestions for future studies.
