论文标题
IC-GVINS：适用于车轮机器人的健壮，实时，以中心的GNSS-Visual惯性导航系统
IC-GVINS: A Robust, Real-time, INS-Centric GNSS-Visual-Inertial Navigation System for Wheeled Robot
论文作者
论文摘要
在这封信中，我们提出了一个适用的实时，实时的，惯性导航系统（INS） - 中心的GNSS-Visual-Visual惯性导航系统（IC-GVIN），用于轮式机器人，其中在状态估计和视觉过程中都可以在该机器人中充分利用精确的INS。为了改善系统的鲁棒性，通过严格的离群策略在整个基于密钥帧的视觉过程中采用了INS信息。采用GNSS来执行IC-GVIN的准确和方便的初始化，并进一步用于在大规模环境中实现绝对定位。 IMU，Visual和GNSS测量值紧密地融合在因子图优化的框架内。进行了专门的实验，以评估轮式机器人上IC-GVIN的鲁棒性和准确性。 IC-GVIN在带有移动对象的各种视觉偏好场景中表现出了出色的鲁棒性。与最先进的视觉惯性导航系统相比，所提出的方法在各种环境中产生了提高的鲁棒性和准确性。我们开源的代码与GitHub上的数据集结合在一起
In this letter, we present a robust, real-time, inertial navigation system (INS)-Centric GNSS-Visual-Inertial navigation system (IC-GVINS) for wheeled robot, in which the precise INS is fully utilized in both the state estimation and visual process. To improve the system robustness, the INS information is employed during the whole keyframe-based visual process, with strict outlier-culling strategy. GNSS is adopted to perform an accurate and convenient initialization of the IC-GVINS, and is further employed to achieve absolute positioning in large-scale environments. The IMU, visual, and GNSS measurements are tightly fused within the framework of factor graph optimization. Dedicated experiments were conducted to evaluate the robustness and accuracy of the IC-GVINS on a wheeled robot. The IC-GVINS demonstrates superior robustness in various visual-degenerated scenes with moving objects. Compared to the state-of-the-art visual-inertial navigation systems, the proposed method yields improved robustness and accuracy in various environments. We open source our codes combined with the dataset on GitHub
