Visual-Inertial Monocular SLAM With Map Reuse
Visual-Inertial Monocular SLAM With Map Reuse
复制标题
DOI：
10.1109/lra.2017.2653359
复制
发表时间：
2017-04-01
影响因子：
5.2
通讯作者：
Tardos, Juan D.
中科院分区：
文献类型：
--
作者：
Mur-Artal, Raul;Tardos, Juan D.
近年来，视觉惯性测距技术取得了很好的成果，其目标是以高精度和鲁棒性计算传感器的增量运动。然而，这些方法缺乏闭环的能力，并且即使传感器不断地重新访问同一地点，轨迹估计也会累积漂移。在这封信中，我们提出了一种新的紧密耦合的视觉惯性同时定位和映射系统，该系统能够闭合循环并重复使用其地图，以实现零漂移定位在已经映射的区域。虽然我们的方法可以应用于任何相机配置，我们在这里解决最普遍的问题，单目相机，其众所周知的规模模糊。我们还提出了一种新的惯性测量单元初始化方法，它计算的规模，重力方向，速度，陀螺仪和加速度计的偏差，在几秒钟内具有高精度。我们在最近的微型飞行器公共数据集的11个序列中测试了我们的系统，实现了1%的典型比例因子误差和厘米精度。我们比较了国家的最先进的视觉惯性里程计序列与重访，证明了更好的精度，我们的方法，由于地图重用和无漂移积累。
In recent years there have been excellent results in visual-inertial odometry techniques, which aim to compute the incremental motion of the sensor with high accuracy and robustness. However, these approaches lack the capability to close loops and trajectory estimation accumulates drift even if the sensor is continually revisiting the same place. In this letter, we present a novel tightly coupled visual-inertial simultaneous localization and mapping system that is able to close loops and reuse its map to achieve zero-drift localization in already mapped areas. While our approach can be applied to any camera configuration, we address here the most general problem of a monocular camera, with its well-known scale ambiguity. We also propose a novel IMU initialization method, which computes the scale, the gravity direction, the velocity, and gyroscope and accelerometer biases, in a few seconds with high accuracy. We test our system in the 11 sequences of a recent micro-aerial vehicle public dataset achieving a typical scale factor error of 1% and centimeter precision. We compare to the state-of-the-art in visual-inertial odometry in sequences with revisiting, proving the better accuracy of our method due to map reuse and no drift accumulation.