Robust 3D scan segmentation for teleoperation tasks in areas contaminated by radiation

3D data collected by a laser scanner has great potential for robotic applications. Exact geometrical models of the environment surrounding the robot can be created from these point clouds. But, before creating any model, the 3D point cloud has to be segmented and depending on the size and quality of the point cloud, this can be a very challenging task. This article describes a robust 3D scan segmentation technique, which is capable of segmenting a 3D point cloud in a short amount of time. The results of the segmentation are used to assist a teleoperator to manoeuvre a robot through an unknown environment. Our segmentation approach copes with indoor and outdoor environments, using only a minimum of assumptions, which makes it very robust. A 3D visualisation illustrates the segmentation results in a clear and user-friendly way.