基于时移IMU预积分的增量视觉惯性初始化时序标定

Bruno Petit, Richard Guillemard, V. Gay-Bellile
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摘要

紧密耦合视觉惯性SLAM (VISLAM)算法是目前室内定位的最先进方法。VISLAM有许多实现,如基于过滤器和基于非线性优化的算法。它们都需要在传感器时钟和初始IMU状态(陀螺仪和加速度计偏差值,重力方向和初始速度)之间进行精确的时间对齐,以进行精确定位。本文提出了一种同时估计IMU摄像机时间定标和IMU初始状态的VISLAM初始化方法。为此,引入了时移IMU预积分(TSIP)测量的概念。一种考虑了传感器时钟偏差影响的IMU预积分插值方法。这些TSIP测量与视觉里程计测量一起包含在增量优化的图形中。在实际数据上的实验表明,该方法可以实现实时、准确和鲁棒的初始化。
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Time Shifted IMU Preintegration for Temporal Calibration in Incremental Visual-Inertial Initialization
Tightly coupled Visual-Inertial SLAM (VISLAM) algorithms are now state of the art approaches for indoor localization. There are many implementations of VISLAM, like filter-based and non-linear optimization based algorithms. They all require an accurate temporal alignment between sensors clock and an initial IMU state gyroscope and accelerometer biases value, gravity direction and initial velocity) for precise localization. In this paper we propose an initialization procedure of VISLAM that estimates simultaneously IMU-camera temporal calibration and the initial IMU state. To this end, the concept of Time Shifted IMU Preintegration} (TSIP) measurements is introduced. an interpolation of IMU preintegration that takes into account the effect of sensors clock misalignment. These TSIP measurements are included along with visual odometry measurements in a graph that is incrementally optimized. It results in a real time, accurate and robust initialization for VISLAM as demonstrated in the experiments on real data.
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