Optimisation of the calibration process of a k-tls based multi-sensor-system by genetic algorithms

In recent years, the requirements in the industrial production of elongated objects, e.g., aircraft, have been increased. An essential aspect of the production process is the 3D object detection as well as the qualitative assessment of the captured data. On the one hand high accuracy requirements with a 3D standard deviation of σ3D = 1 mm have to be fulfilled, on the other hand an efficient 3D object capturing is needed. In terms of efficiency, kinematic terrestrial laser scanning (k-TLS) has proven its strength in the recent years. It can be seen as an alternative and is even more powerful than to the well established static terrestrial laser scanning (s-TLS). In order to perform a high accurate 3D object capturing with k-TLS, the 3D object capturing of the initial sensor, the (geo-)referencing of the mobile platform, the synchronisation of all sensors and the system calibration, which means the determination of six extrinsic parameters have to be performed with suitable accuracy. Within this contribution we focus on the system calibration. Therefore an approach based on known reference geometries, here planes, is used (Strübing and Neumann, 2013). As a result, the lever arm and boresight angles are determined. Hereby the number as well as the position and orientation of the reference geometries is of importance. Therefore, an optimal arrangement has to be found. Here a sensitive analysis based on uncertainty propagation is used. A selective search of an optimised arrangement is carried out by a genetic algorithm. Within some examples we demonstrate some theoretical aspects and how an optimisation of the reference geometry arrangement can be achieved.