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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6
MONODA: A Neural Modular Architecture for Obstacle Avoidance without Knowledge of the Environment
Como, Italy
July 24-July 27
ISBN: 0-7695-0619-4
ASCII Text
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Catarina Silva, Manuel Crisóstomo, Bernardete Ribeiro, "MONODA: A Neural Modular Architecture for Obstacle Avoidance without Knowledge of the Environment," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 6, pp. 6334, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6, 2000.
 
 
BibTex
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@article{ 10.1109/IJCNN.2000.859418,
author = {Catarina Silva and Manuel Crisóstomo and Bernardete Ribeiro},
title = {MONODA: A Neural Modular Architecture for Obstacle Avoidance without Knowledge of the Environment},
journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on},
volume = {6},
year = {2000},
issn = {1098-7576},
pages = {6334},
doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.859418},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Neural Networks, IEEE - INNS - ENNS International Joint Conference on
TI - MONODA: A Neural Modular Architecture for Obstacle Avoidance without Knowledge of the Environment
SN - 1098-7576
SP
EP
A1 - Catarina Silva,
A1 - Manuel Crisóstomo,
A1 - Bernardete Ribeiro,
PY - 2000
KW - Neural networks
KW - modularity
KW - mobile robotics
VL - 6
JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on
ER -
 
Catarina Silva, Universidade de Coimbra and Escola Superior de Tecnologia e Gest?o - Leiria
Manuel Crisóstomo, Instituto de Sistemas e Rob?tica - Coimbra
Bernardete Ribeiro, Universidade de Coimbra
A new technique is proposed to detect and avoid obstacles for a mobile robot in an unknown environment. The usual problem of having too much sensorial information is dealt with by using several neural networks that cooperate in the guidance of the robot. Several unknown obstacle configurations were presented to the modular networks, proving that the MONODA architecture is very effective for obstacle avoidance when there is neither a priori nor a posteriori map of the environment.
Index Terms:
Neural networks, modularity, mobile robotics
Citation:
Catarina Silva, Manuel Crisóstomo, Bernardete Ribeiro, "MONODA: A Neural Modular Architecture for Obstacle Avoidance without Knowledge of the Environment," ijcnn, vol. 6, pp.6334, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6, 2000
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