On the design of intelligent robotic agents for assembly

Authors:
I. Lopez-Juarez;J. Corona-Castuera;M. Peña-Cabrera;K. Ordaz-Hernandez
Affiliations:
CIATEQ A.C., Centro de Tecnologıa Avanzada, Manantiales 23A, Fracc. Ind. B.Q., El Marques, Querétaro, CP 76246, Mexico;CIATEQ A.C., Centro de Tecnologıa Avanzada, Manantiales 23A, Fracc. Ind. B.Q., El Marques, Querétaro, CP 76246, Mexico;Departmento de Ingenierıa en Sistemas Computacionales y Automatización, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas (IIMAS), Universidad Nacional Autonoma de ...;CIATEQ A.C., Centro de Tecnologıa Avanzada, Manantiales 23A, Fracc. Ind. B.Q., El Marques, Querétaro, CP 76246, Mexico
Venue:
Information Sciences: an International Journal
Year:
2005

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Abstract

Robotic agents can greatly be benefited from the integration of perceptual learning in order to monitor and adapt to changing environments. To be effective in complex unstructured environments, robots have to perceive the environment and adapt accordingly. In this paper it is discussed a biology inspired approach based on the adaptive resonance theory (ART) and implemented on an KUKA KR15 industrial robot during real-world operations (e.g. assembly operations). The approach intends to embed naturally the skill learning capability during manufacturing operations (i.e., within a flexible manufacturing system). The integration of machine vision and force sensing has been useful to demonstrate the usefulness of the cognitive architecture to acquire knowledge and to effectively use it to improve its behaviour. Practical results are presented, showing that the robot is able to recognise a given component and to carry out the assembly. Adaptability is validated by using different component geometry during assemblies and also through skill learning which is shown by the robot's dexterity.