Robot vision with cellular neural networks:: A practical implementation of new algorithms

被引：14
作者：
Egidio Pazienza, Giovanni
Ponce-Garcia, Xavier
Balsi, Marco
Vilasis-Cardona, Xavier
机构：
[1] Univ Ramon Llull, Dept Elect Engn & Arquitectura La Salle, Barcelona 08022, Spain
[2] Univ Roma La Sapienza, Dipartimento Ingn Elettron, I-00184 Rome, Italy
来源：
INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS | 2007年 / 35卷 / 04期
关键词：
artificial vision; autonomous robot; CNN; tracking; obstacle avoidance;
D O I：
10.1002/cta.395
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Cellular neural networks (CNNs) are well suited for image processing due to the possibility of a parallel computation. In this paper, we present two algorithms for tracking and obstacle avoidance using CNNs. Furthermore, we show the implementation of an autonomous robot guided using only real-time visual feedback; the image processing is performed entirely by a CNN system embedded in a digital signal processor (DSP). We successfully tested the two algorithms on this robot. Copyright (c) 2006 John Wiley & Sons, Ltd.
引用
收藏
页码：449 / 462
页数：14
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