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Vision based algorithm for path planning of a mobile robot by using cellular neural networks

The paper presents a new vision based algorithm for mobile robots path planning in an environment with obstacles. Cellular neural networks (CNNs) processing techniques are used here for real time motion planning to reach a fixed target. The CNN methods have been considered a solution for image processing in autonomous mobile robots guidance. The choice of CNNs for the visual processing is based on the possibility of their hardware implementation in large networks on a single VLSI chip (cellular neural networks -universal machine, CNN-UM (Roska and Chua, 1993 and Kim et al., 2002))