A Comparison of LiDAR-based SLAM Systems for Control of Unmanned Aerial Vehicles
It addresses the problem of selecting effective SLAM methods for UAV control, but is incremental as it compares existing systems without introducing new algorithms.
This paper compared three LiDAR-based SLAM systems (Cartographer, LOAM, HDL graph SLAM) for pose feedback in autonomous UAV flight, finding that they produced high-quality pose estimates and were integrated into a control system with performance evaluated using step response and trajectory error metrics.
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.