A CNN-based passive optical range finder for real-time robotic applications

Abstract

The paper presents a new cellular neural network (CNN) for real-time stereo vision, useful as a passive optical range finder for autonomous robots and vehicles. The stereo matching as energy minimization is discussed, and former neural approaches to the problem are analyzed. Experimental results with the new CNN both with synthetic and real images are reported, demonstrating the performance of the system.