论文标题
通过正摩萨图将空中和地面移动机器人的合作定位
Collaborative Localization of Aerial and Ground Mobile Robots through Orthomosaic Map
论文作者
论文摘要
随着对SLAM系统的研究加深，已经提出了与多机器人合作大满贯的可能性。考虑到空中系统的合作大满贯，本文提出了一种地图匹配和本地化方法。所提出的方法旨在帮助精确匹配两个独立系统构建的地图，这些系统具有相同路线的观点的较大范围，并最终使地面移动机器人可以将自身定位于无人机给出的全局地图中。它包含具有高程图和软件“ MetaShape”的密集映射，与所提出的模板匹配匹配算法，加权归一化互相关（WNCC）以及与粒子过滤器的定位。该方法可以使合作大满贯的地图与多个场景传感器的可行性（从立体相机到激光镜头不同），并且对两个系统的同步不敏感。我们证明了在空气地面数据集的实验下的准确性，鲁棒性和方法的速度。
With the deepening of research on the SLAM system, the possibility of cooperative SLAM with multi-robots has been proposed. This paper presents a map matching and localization approach considering the cooperative SLAM of an aerial-ground system. The proposed approach aims to help precisely matching the map constructed by two independent systems that have large scale variance of viewpoints of the same route and eventually enables the ground mobile robot to localize itself in the global map given by the drone. It contains dense mapping with Elevation Map and software "Metashape", map matching with a proposed template matching algorithm, weighted normalized cross-correlation (WNCC) and localization with particle filter. The approach enables map matching for cooperative SLAM with the feasibility of multiple scene sensors, varies from stereo cameras to lidars, and is insensitive to the synchronization of the two systems. We demonstrate the accuracy, robustness, and the speed of the approach under experiments of the Aero-Ground Dataset.
