论文标题
野猫：在线连续时间3D激光射击
Wildcat: Online Continuous-Time 3D Lidar-Inertial SLAM
论文作者
论文摘要
我们提出了Wildcat，这是一种新颖的在线3D LIDAR惯性大满贯系统，具有出色的多功能性和鲁棒性。野猫以其核心结合了一个强大的实时激光惯性射音频学模块，利用连续的时间轨迹表示形式和有效的姿势图形优化模块，该模块无缝地支持单个和多区域的设置。最近在DARPA地下挑战中证明了野猫的鲁棒性，在这种挑战中，它表现出在各种类型的衰落和感知挑战性的环境中的其他大满贯系统。在本文中，我们在一套新的公开可用的现实世界数据集中广泛评估了野猫，并与两个现有的最先进的LIDAR惯性惯性SLAM系统相比，其优异的鲁棒性和多功能性。
We present Wildcat, a novel online 3D lidar-inertial SLAM system with exceptional versatility and robustness. At its core, Wildcat combines a robust real-time lidar-inertial odometry module, utilising a continuous-time trajectory representation, with an efficient pose-graph optimisation module that seamlessly supports both the single- and multi-agent settings. The robustness of Wildcat was recently demonstrated in the DARPA Subterranean Challenge where it outperformed other SLAM systems across various types of sensing-degraded and perceptually challenging environments. In this paper, we extensively evaluate Wildcat in a diverse set of new and publicly available real-world datasets and showcase its superior robustness and versatility over two existing state-of-the-art lidar-inertial SLAM systems.
