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Proceedings Paper

Cellular neural networks and biologically inspired motion control
Author(s): Paolo Arena; Luigi Fortuna
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Paper Abstract

12 The main purpose of this paper is to present the Cellular Neural Network (CNN) Paradigm as a powerful strategy to design and to implement in hardware efficient locomotion control techniques. A gallery of biologically inspired walking robots are presented. Moreover, the availability of efficient distributed control structures needs a sensing capability of the same efficiency. Therefore the sensing stage is performed by using once again the CNN paradigm, but used as fast image processors. The strategy is supported by the fact that CNN devices with on-chip optical sensors are currently being tested and will be soon available. In such a way, images are acquired by a video camera with a CNN image processing device, able to extract the key features. These ones represent the `command' to take on the right locomotion pattern. Since all the methodology is realized by using analog processors, the whole strategy represents a real breakthrough in the smart sensing and control field.

Paper Details

Date Published: 12 February 2001
PDF: 12 pages
Proc. SPIE 4190, Optomechatronic Systems, (12 February 2001); doi: 10.1117/12.417229
Show Author Affiliations
Paolo Arena, Univ. degli Studi di Catania (Italy)
Luigi Fortuna, Univ. degli Studi di Catania (Italy)


Published in SPIE Proceedings Vol. 4190:
Optomechatronic Systems
Hyungsuck Cho; George K. Knopf, Editor(s)

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