论文标题
弹性符合连续时间：以地图为中心的密度3D激光雷达大满贯
Elasticity Meets Continuous-Time: Map-Centric Dense 3D LiDAR SLAM
论文作者
论文摘要
以地图为中心的大满贯利用弹性作为循环闭合的手段。与以轨迹为中心的大满贯方法相比，这种方法降低了循环闭合成本，而仍然提供了大规模融合的密集地图。在本文中，我们提出了一个基于3D激光雷达以地图为中心的大满贯的新型框架。我们的方法具有以MAP为中心的方法的优点，展示了与多模式传感器融合和LIDAR运动失真相关的现有系统缺点的新功能。这是通过使用局部连续时间（CT）轨迹表示来实现的。同样，我们的表面分辨率防腐剂匹配算法和基于WishArt的表面融合模型可实现非冗余但密集的映射。此外，我们提出了一个可靠的度量环闭合模型，以使该方法稳定，无论循环闭合发生何处。最后，我们使用多个传感器有效负载配置和环境来说明其实用性和鲁棒性，通过模拟和真实数据实验来证明我们的方法。
Map-centric SLAM utilizes elasticity as a means of loop closure. This approach reduces the cost of loop closure while still provides large-scale fusion-based dense maps, when compared to the trajectory-centric SLAM approaches. In this paper, we present a novel framework for 3D LiDAR-based map-centric SLAM. Having the advantages of a map-centric approach, our method exhibits new features to overcome the shortcomings of existing systems, associated with multi-modal sensor fusion and LiDAR motion distortion. This is accomplished through the use of a local Continuous-Time (CT) trajectory representation. Also, our surface resolution preservative matching algorithm and Wishart-based surfel fusion model enables non-redundant yet dense mapping. Furthermore, we present a robust metric loop closure model to make the approach stable regardless of where the loop closure occurs. Finally, we demonstrate our approach through both simulation and real data experiments using multiple sensor payload configurations and environments to illustrate its utility and robustness.
