论文标题
无人机系统的全球最佳孔径对齐
Globally Optimal Boresight Alignment of UAV-LiDAR Systems
论文作者
论文摘要
在空气中的光检测和范围（激光雷达）系统中，安装在无人机（UAV）框架上的激光扫描仪与惯性导航系统（INS）之间的未对准可能导致3D点云。确定方向偏移，或疏忽误差是许多基于激光雷达的应用程序的关键。在这项工作中，我们引入了一个混合兼具四局部约束二次计划（MIQCQP），该程序可以在全球范围内解决这个未对准问题。我们还提出了一个嵌套的空间分支和绑定（NSBB）算法，以改善计算性能。 NSBB依赖于新的预处理步骤，这些步骤逐渐减少了问题的大小。此外，提出了允许我们快速启发式解决方案的自适应网格搜索（AGS）。我们的算法是开源，多线程和多机兼容的。
In airborne light detection and ranging (LiDAR) systems, misalignments between the LiDAR-scanner and the inertial navigation system (INS) mounted on an unmanned aerial vehicle (UAV)'s frame can lead to inaccurate 3D point clouds. Determining the orientation offset, or boresight error is key to many LiDAR-based applications. In this work, we introduce a mixed-integer quadratically constrained quadratic program (MIQCQP) that can globally solve this misalignment problem. We also propose a nested spatial branch and bound (nsBB) algorithm that improves computational performance. The nsBB relies on novel preprocessing steps that progressively reduce the problem size. In addition, an adaptive grid search (aGS) allowing us to obtain quick heuristic solutions is presented. Our algorithms are open-source, multi-threaded and multi-machine compatible.
