TY - JOUR
T1 - Guiding a mobile robot with cellular neural networks
AU - Vilasís-Cardona, Xavier
AU - Luengo, Sonia
AU - Solsona, Jordi
AU - Maraschini, Alessandro
AU - Apicella, Giada
AU - Balsi, Marco
PY - 2002/11
Y1 - 2002/11
N2 - We show how cellular neural networks (CNNs) are capable of providing the necessary signal processing needed for visual navigation of an autonomous mobile robot. In this way, even complex feature detection and object recognition can be obtained in real time by analogue hardware, making fully autonomous real-time operation feasible. An autonomous robot was first simulated and then implemented by simulating the CNN with a DSP. The robot is capable of navigating in a maze following lines painted on the floor. Images are processed entirely by a CNN-based algorithm, and navigation is controlled by a fuzzy-rule-based algorithm.
AB - We show how cellular neural networks (CNNs) are capable of providing the necessary signal processing needed for visual navigation of an autonomous mobile robot. In this way, even complex feature detection and object recognition can be obtained in real time by analogue hardware, making fully autonomous real-time operation feasible. An autonomous robot was first simulated and then implemented by simulating the CNN with a DSP. The robot is capable of navigating in a maze following lines painted on the floor. Images are processed entirely by a CNN-based algorithm, and navigation is controlled by a fuzzy-rule-based algorithm.
KW - Artificial vision
KW - Autonomous robots
KW - Cellular neural networks
UR - http://www.scopus.com/inward/record.url?scp=0036860915&partnerID=8YFLogxK
U2 - 10.1002/cta.212
DO - 10.1002/cta.212
M3 - Article
AN - SCOPUS:0036860915
SN - 0098-9886
VL - 30
SP - 611
EP - 624
JO - International Journal of Circuit Theory and Applications
JF - International Journal of Circuit Theory and Applications
IS - 6
ER -