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.
翻译:我们展示了野猫,这是一个新的在线 3D Lidar-nestial SLM 系统,具有非凡的多功能性和强健性。野猫的核心是,将一个强大的实时利达尔-内皮奥多米模型组合在一起,使用一个连续的轨迹代表器,同时使用一个高效的成形图优化模块,无缝地支持单一和多试剂环境。野猫的强健性最近在DARPA Subterrane 挑战中得到了证明,它超越了其他的SLM系统,跨越了各种遥感失能和感知上具有挑战性的环境。在本文中,我们广泛评价野猫在一套多样的新的和公开存在的真实世界数据集中,并展示了它优异的强健性和多功能性,超越了两个现有最先进的里氏内皮层系统。