Establishment of a New Quantitative Evaluation Model of the Targetsxe2x80x99 Geometry Distribution for Terrestrial Laser Scanning The precision of targetbased registration is related to the geometry distribution of targets, while the current method of setting the targets mainly depends on experience, and the impact is only evaluated qualitatively by the findings from empirical experiments and through simulations. In this paper, we propose a new quantitative evaluation model, which is comprised of the rotation dilution of precision (    r D O P    , assessing the impact of targetsxe2x80x99 geometry distribution on the rotation parameters) and the translation dilution of precision (    t D O P    , assessing the impact of targetsxe2x80x99 geometry distribution on the translation parameters). Here, the definitions and derivation of relevant formulas of the     r D O P     and     t D O P     are given, the experience conclusions are theoretically proven by the model of     r D O P     and     t D O P    , and an accurate method for determining the optimal placement location of targets and the scanner is proposed by calculating the minimum value of     r D O P     and     t D O P    . Furthermore, we can refer to the model (    r D O P     and     t D O P    ) as a unified model of the geometric distribution evaluation model, which includes the     D O P     model in GPS.

3D LiDAR Extrinsic Calibration Method using Ground Plane Model Estimation In the context of road defects detection, especially potholes detection, using a 3D LiDAR mounted on a vehicle seems to be an interesting way to provide location and geometric information about the defects. In this paper, an extrinsic calibration method is proposed, to merge all the LiDAR frames in a common reference frame and to define the positioning of the sensor. This method depends mainly on the geometrical ground impact model in order to estimate the LiDAR extrinsic parameters by successive steps algorithm: fitting plane, Euleru0027s angles estimation of rotation, height estimation and parameters optimization. Results are presented in terms of precision and robustness against the LiDAR range accuracy proving the performance of this calibration method.