Ein echtzeitfähiges System zur Gewinnung von Tiefeninformation aus Stereobildpaaren für konfigurierbare Hardware

This work presents a realtime stereo image matching system that takes advantage of a global image matching method. The system is designed to provide depth information for mobile robotic applications. Typical tasks of the proposed system are to assist in obstacle avoidance, SLAM and path planning of mobile robots, that pose strong requirements on the size, energy consumption, reliability, frame rate and quality of the calculated depth map. Current available systems either rely on active sensors or on local stereo-image matching algorithms. The first are only suitable in controlled environments while the second suffer from low quality depth-maps. Top ranking quality results are only achieved by an iterative approach using global image matching and colour segmentation techniques which are computationally demanding and therefore difficult to be executed in real time. Attempts were made to still reach real-time performance with global methods by simplifying the routines but led to degraded depth maps which are at the end almost comparable with local methods. An equally named semi-global algorithm was proposed earlier, that shows both very good image matching results and relatively simple execution at the same time. A memory efficient variant of the Semi-Global Matching algorithm is presented and adopted for an implementation based on reconfigurable hardware that is suitable for real-time operations in the field of robotics. It will be shown that the modified version of the efficient SemiGlobal matching method is delivering equivalent result compared to the original algorithm. The complete design has been implemented within a hardware development framework that is also reviewed.