Ismael Lopez-Juarez

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This article presents a new learning methodology based on a hybrid algorithm for interval type-2 TSK fuzzy logic systems (FLS). Using input-output data pairs during the forward pass of the training process, the interval type-2 TSK FLS output is calculated and the consequent parameters are estimated by recursive least-squares (RLS) method. In the backward(More)
Mechanical assembly by robots has traditionally depended on simple sensing systems and the robot manufacturers programming language. However, this restricts the use of robots in complex manufacturing operations. An alternative to robot programming is the creation of self-adaptive robots based on the adaptive resonance theory (ART) artificial neural network(More)
In this chapter we describe the general framework design for a distributed architecture to integrate multiple sensorial capabilities within an intelligent manufacturing system for assembly. We will formally define the model of the M2ARTMAP multimodal architecture. We present some simulated results of the model using a public domain multimodal data base.(More)
A new learning methodology based on a hybrid algorithm for interval type-2 fuzzy logic systems (FLS) parameter estimation is presented. The new proposal consists of Back-Propagation with Recursive Least-Squares (BP-RLS) and BackPropagation with square-root filter (BP-REFIL). A system with the proposed methodology was simulated to test its capability for(More)
In previous chapter it has been described the overall architecture for multimodal learning in the robotic assembly domain (Lopez-Juarez & Rios-Cabrera, 2006). The acquisition of assembly skills by robots is greatly supported by the effective use of contact force sensing and objects recognition. In this chapter, we will describe the robot’s ability to(More)