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

Author

Gavrilut, I. ; Gacsádi, A. ; Grava, C. ; Tiponut, V.

Author_Institution

Dept. of Electron., Oradea Univ.

Volume

2

fYear

2006

fDate

25-28 May 2006

Firstpage

306

Lastpage

311

Abstract

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))

Keywords

cellular neural nets; collision avoidance; control engineering computing; mobile robots; robot vision; VLSI chip; autonomous mobile robot guidance; cellular neural network; hardware implementation; image processing; mobile robot path planning; vision based algorithm; Cellular neural networks; Circuits; Image processing; Infrared sensors; Mobile robots; Neural network hardware; Path planning; Sensor arrays; Trajectory; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation, Quality and Testing, Robotics, 2006 IEEE International Conference on

Conference_Location

Cluj-Napoca

Print_ISBN

1-4244-0360-X

Electronic_ISBN

1-4244-0361-8

Type

conf

DOI

10.1109/AQTR.2006.254650

Filename

4022973