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This paper introduces a method for calibrating LiDAR-IMU systems on tilted surfaces, overcoming the limitations of existing techniques that assume flat ground. By utilizing ground-plane residuals that do not rely on the colinearity of gravity and surface normal vectors, the method enhances calibration accuracy in non-flat environments. Experimental results on datasets from both a Husky ground vehicle and an off-road vehicle demonstrate significant improvements in repeatability, particularly for tilted surfaces.
Calibration accuracy for LiDAR-IMU systems can be dramatically improved on tilted surfaces, challenging the long-held assumption that flat ground is necessary for effective sensor alignment.
This paper presents a novel method that extends targetless LiDAR-IMU calibration for ground vehicles to non- flat environments. Calibration typically necessitates full exci- tation of the sensor rig, a requirement that is not fulfilled by ground vehicles in normal operation. To address the degenerate planar motion, state-of-the-art methods propose residuals that assume the colinearity of the gravity and physical surface normal vectors, restricting usage to cases where the ground is assumed flat. This paper proposes ground-plane residuals that do not require this assumption, and are applicable for planar motion on a tilted surface. Results are demonstrated on a dataset collected from a Husky ground vehicle, on the M2DGR dataset, as well as on an offroad vehicle dataset. Repeatability is shown to be improved both in tilted and flat-ground scenarios, with strong improvement demonstrated for the tilted case. The implementation and experiments are open-sourced at https://github.com/vkorotkine/licalib_tilted_ground.
