Alejandra Barrera

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p. 1 Abstract—This paper presents a robot architecture with spatial cognition and navigation capabilities that captures some properties of the rat brain structures involved in learning and memory. This architecture relies on the integration of kinesthetic and visual information derived from artificial landmarks, as well as on Hebbian learning, to build a(More)
The study of behavioral and neurophysiological mechanisms involved in rat spatial cognition provides a basis for the development of computational models and robotic experimentation of goal-oriented learning tasks. These models and robotics architectures offer neurobiologists and neuroethologists alternative platforms to study, analyze and predict spatial(More)
Sensory-motor coordination involves the study of how organisms make accurate goaldirected movements based on perceived sensory information. There are two problems associated to this process: sensory feedback is noisy and delayed, which can make movements inaccurate and unstable, and the relationship between a motor command and the movement it produces is(More)
In this paper we present a model designed on the basis of the rat's brain neurophysiology to provide a robot with spatial cognition and goal-oriented navigation capabilities. We describe place representation and recognition processes in rats as the basis for topological map building and exploitation by robots. We experiment with the model by training a(More)
The study of spatial memory and learning in rats has inspired the development of multiple computational models that have lead to novel robotics architectures. Evaluation of computational models and resulting robotic architecture is usually carried out at the behavioral level by evaluating experimental tasks similar to those performed with rats. While(More)
Anticipation of sensory consequences of actions is critical for the predictive control of movement that explains most of our sensory-motor behaviors. Plenty of neuroscientific studies in humans suggest evidence of anticipatory mechanisms based on internal models. Several robotic implementations of predictive behaviors have been inspired on those biological(More)
ing and non-profit use of the material is permitted with credit to the source. Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published articles. Publisher assumes no responsibility(More)
About the reviewer M. Sami Fadali earned a BS in Electrical Engineering from Cairo University in 1974, an MS from the Control Systems Center, UMIST, England, in 1977 and a Ph.D. from the University of Wyoming in 1980. He was an Assistant Professor of Electrical Engineering at the University of King Abdul Aziz, Jeddah, Saudi Arabia, 1981–1983. From(More)