论文标题
Dynavig：单眼视觉/ins/gnss在动态场景中的AGV集成导航和对象跟踪
DynaVIG: Monocular Vision/INS/GNSS Integrated Navigation and Object Tracking for AGV in Dynamic Scenes
论文作者
论文摘要
视觉惯性进程（VIO）通常会在长期运行中漂移，精度很容易受到动态对象的影响。我们提出了基于单眼视觉，惯性导航系统（INS）和全球导航卫星系统（GNSS）的集成的导航和对象跟踪系统。我们的系统旨在在动态场景中对自动化地面车辆（AGV）的导航状态（AGV）进行准确的全球估计。由于对象的规模歧义，因此提出了先前的高度模型来初始化对象姿势，并在GNSS和ins的帮助下连续估计量表。为了准确地通过复杂的移动跟踪对象，我们根据其运动状态建立准确的动力学模型。然后在统一框架中优化了多传感器观测值。 Kitti数据集上的实验表明，与最新方法相比，多传感器融合可以有效地提高导航和对象跟踪的准确性。此外，提出的系统还可以对改变速度或方向的对象进行良好的估计。
Visual-Inertial Odometry (VIO) usually suffers from drifting over long-time runs, the accuracy is easily affected by dynamic objects. We propose DynaVIG, a navigation and object tracking system based on the integration of Monocular Vision, Inertial Navigation System (INS), and Global Navigation Satellite System (GNSS). Our system aims to provide an accurate global estimation of the navigation states and object poses for the automated ground vehicle (AGV) in dynamic scenes. Due to the scale ambiguity of the object, a prior height model is proposed to initialize the object pose, and the scale is continuously estimated with the aid of GNSS and INS. To precisely track the object with complex moving, we establish an accurate dynamics model according to its motion state. Then the multi-sensor observations are optimized in a unified framework. Experiments on the KITTI dataset demonstrate that the multisensor fusion can effectively improve the accuracy of navigation and object tracking, compared to state-of-the-art methods. In addition, the proposed system achieves good estimation of the objects that change speed or direction.
