  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.
