On the design of a multimodal cognitive architecture for perceptual learning in industrial robots

Authors:
Ismael Lopez-Juarez;Keny Ordaz-Hernández;Mario Peña-Cabrera;Jorge Corona-Castuera;Reyes Rios-Cabrera
Affiliations:
CIATEQ A.C. Advanced Technology Centre, El Marques, Queretaro, Mexico;,CIATEQ A.C. Advanced Technology Centre, El Marques, Queretaro, Mexico;Instituto de Investigaciones en Matemáticas Aplicadas y Sistemas IIMAS-UNAM, Circuito Escolar, Cd. Universitaria, Mexico DF;CIATEQ A.C. Advanced Technology Centre, El Marques, Queretaro, Mexico;CIATEQ A.C. Advanced Technology Centre, El Marques, Queretaro, Mexico
Venue:
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Year:
2005

Citing 4
Cited 1

Data Fusion for Sensory Information Processing Systems

Data Fusion for Sensory Information Processing Systems
ARTMAP neural networks for information fusion and data mining: map production and target recognition methodologies

Neural Networks
Cascade ARTMAP: integrating neural computation and symbolic knowledge processing

IEEE Transactions on Neural Networks
MART: a multichannel ART-based neural network

IEEE Transactions on Neural Networks

Behaviour-based approach for skill acquisition during assembly operations, starting from scratch

Robotica

Quantified Score

Hi-index	0.00

Visualization

Abstract

Robots can be greatly benefited from the integration of artificial senses in order to adapt to changing worlds. To be effective in complex unstructured environments robots have to perceive the environment and adapt accordingly. In this paper, it is introduced a biology inspired multimodal architecture called M2ARTMAP which is based on the biological model of sensorial perception and has been designed to be a more versatile alternative to data fusion techniques and non-modular neural architectures. Besides the computational overload compared to FuzzyARTMAP, M2ARTMAP reaches similar performance. This paper reports the results found in simulated environments and also the observed results during assembly operations using an industrial robot provided with vision and force sensing capabilities.