论文标题
与在线校准和初始化紧密耦合的基于优化的GPS-Visual-Visual-Visual惯性进程
Tightly Coupled Optimization-based GPS-Visual-Inertial Odometry with Online Calibration and Initialization
论文作者
论文摘要
在本文中，我们提出了一个紧密耦合的基于优化的GPS-Visual-Visual惯性进程系统，以求解视觉惯性渗透量的轨迹漂移，尤其是在长期运行期间。在局部束调节中共同最大程度地降低了视觉再现残差，IMU残差和GPS测量残差，其中我们应用了GPS测量值，IMU预一整合用于IMU残留物来制定新型GPS残差。为了提高系统的效率和鲁棒性，我们提出了一种快速参考帧初始化方法以及用于GPS-IMU外部和时间偏移的在线校准方法。此外，我们进一步测试了在线校准方法的性能和收敛性。 Euroc数据集的实验结果表明，我们的方法始终优于其他紧密耦合和松散耦合的方法。同时，该系统已在KAIST数据集上进行了验证，该系统证明我们的系统在视觉或GPS失败的情况下可以很好地工作。
In this paper, we present a tightly coupled optimization-based GPS-Visual-Inertial odometry system to solve the trajectory drift of the visual-inertial odometry especially over long-term runs. Visual reprojection residuals, IMU residuals, and GPS measurement residuals are jointly minimized within a local bundle adjustment, in which we apply GPS measurements and IMU preintegration used for the IMU residuals to formulate a novel GPS residual. To improve the efficiency and robustness of the system, we propose a fast reference frames initialization method and an online calibration method for GPS-IMU extrinsic and time offset. In addition, we further test the performance and convergence of our online calibration method. Experimental results on EuRoC datasets show that our method consistently outperforms other tightly coupled and loosely coupled approaches. Meanwhile, this system has been validated on KAIST datasets, which proves that our system can work well in the case of visual or GPS failure.
