Sliding-Window Adjustment for Monocular Simultaneous Localization and Mapping

J. Meidow, Markus Kleinert, D. Bulatov
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Abstract

Cameras are appealing sensors for airborne applications, since they measure passively and are small, lightweight, and inexpensive. Compared to other sensors used for navigation, they feature complementary error characteristics. They capture the environment, and hence provide observations for the solution of the problem commonly referred to as simultaneous localization and mapping. In photogrammetry, bundle adjustment is known to provide optimal estimates for simultaneous scene reconstruction and pose estimation. A sliding-window adjustment is presented that features real-time capability: that is, a continuous video stream can be processed by the usually limited onboard resources of an unmanned aerial vehicle. Having airborne applications in mind, a parametrization for unknown three-dimensional points is incorporated that is able to represent points located far away from the camera or even at infinity. Due to the delayed initialization of these points, the need for prior information about the depths of the...
单目同时定位和映射的滑动窗口调整
相机是机载应用中很有吸引力的传感器,因为它们是被动测量的,而且体积小、重量轻、价格便宜。与其他用于导航的传感器相比,它们具有互补的误差特性。它们捕获环境,并因此为通常称为同步定位和映射的问题的解决方案提供观察。在摄影测量中,束调整被认为是同时提供场景重建和姿态估计的最佳估计。提出了一种具有实时性的滑动窗口调节方法,即可以利用无人机有限的机载资源处理连续视频流。考虑到机载应用,未知三维点的参数化被纳入其中,能够表示远离相机甚至无限远的点。由于这些点的初始化延迟,需要关于点深度的先验信息。
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