This paper investigates the use of LiDAR SLAM as a pose feedback for autonomous flight. Cartographer, LOAM and HDL graph SLAM are first introduced on a conceptual level and later tested for this role. They are first compared offline on a series of datasets to see if they are capable of producing high-quality pose estimates in agile and long-range flight scenarios. The second stage of testing consists of integrating the SLAM algorithms into a cascade PID UAV control system and comparing the control system performance on step excitation signals and helical trajectories. The comparison is based on step response characteristics and several time integral performancecriteria as well as the RMS error between planned and executed trajectory.
翻译:本文件调查使用LiDAR SLAM作为自动飞行反馈工具的情况,制图员、LOAM和HDL图形SLAM首先在概念层面推出,后来又对这一作用进行了测试,首先在一系列数据集上进行离线比较,以确定它们是否能够在灵活和远程飞行情景中提出高质量的构成估计,第二阶段测试包括将SLAM算法纳入级联PIDUAV控制系统,比较步骤引力信号和直升机轨迹的控制系统性能,比较的依据是步骤响应特征和若干时间整体性能标准以及计划轨道与实际轨道之间的RMS错误。