Improving plane extraction from 3D data by fusing laser data and vision

The problem of extracting three-dimensional structures from data acquired with mobile robots has received considerable attention over the past years. Robots that are able to perceive their three-dimensional environment are envisioned to more robustly perform tasks like navigation, rescue, and manipulation. In this paper we present an approach that simultaneously uses color and range information to cluster 3D points into planar structures. Our current system also is able to calibrate the camera and the laser based on the remission values provided by the range scanner and the brightness of the pixels in the image. It has been implemented on a mobile robot equipped with a manipulator that carries a range scanner and a camera for acquiring colored range scans. Several experiments carried out on real data and in simulations demonstrate that our approach yields highly accurate results also in comparison with previous approaches.