Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 449-462 |
| Number of pages | 14 |
| Journal | International Journal of Circuit Theory and Applications |
| Volume | 35 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Jul 2007 |
Keywords
- Artificial vision
- Autonomous robot
- CNN
- Obstacle avoidance
- Tracking
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