Year:  2003

To obtain 3D environmental data the Institute for Systems Engineering has developed a continuously rotating 3D scanner consisting of a Scan Drive system especially designed for this application and a SICK laser scanner. The sensor can be used on mobile robot platforms for environmental perception and navigation. It can take a complete picture of its surroundings every 2 seconds with more than 13,000 measuring points to be taken into account every second. These points are synchronized with the angle of the rotation 2D scanner and the actual position and location of the robot to generate accurate 3D data even during the robot's journey. Evaluation of the data obtained is performed via a Scalable Processing Box (SPB) on the basis of our robot operating system. Using this real time operating system it is possible to avoid systematic measurement errors which usually occur due to runtime differences during data processing. The 3D point clouds obtained are evaluated using different algorithms. In this context, algorithms are available which recognize the obstacles in 3D pictures reducing the gathered information about size and orientation of the objects to a twodimensional view. Then, these data can be fed to the 2D SLAM algorithms thus enabling us to use the considerably higher amount of information contained in 3D scans to have 2D algorithms work more effectively. Integrating 3D perception makes it possible - for the first time - to autonomously navigate in an unstructured outdoor environment. Furthermore we work on extracting characteristics within the 3D point clouds to finally examine the 3D data as to certain features, thus reducing the large quantities of data generated by the 3D sensor and implementing more efficient algorithms for object detection and classification.