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Biologically-inspired robot spatial cognition based on rat neurophysiological studies

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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 holistic topological-metric spatial representation during exploration, and employs reinforcement learning by means of an Actor-Critic architecture to enable learning and unlearning of goal locations. From a robotics perspective, this work can be placed in the gap between mapping and map exploitation currently existent in the SLAM literature. The exploitation of the cognitive map allows the robot to recognize places already visited and to find a target from any given departure location, thus enabling goal-directed navigation. From a biological perspective, this study aims at initiating a contribution to experimental neuroscience by providing the system as a tool to test with robots hypotheses concerned with the underlying mechanisms of rats’ spatial cognition. Results from different experiments with a mobile AIBO robot inspired on classical spatial tasks with rats are described, and a comparative analysis is provided in reference to the reversal task devised by O’Keefe in 1983.

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Authors and Affiliations

  1. Computer Engineering Department, Robotics and CANNES Laboratories at the Instituto Tecnológico Autónomo de México, Río Hondo #1, Tizapán San Ángel, CP 01000, México DF, Mexico

    Alejandra Barrera & Alfredo Weitzenfeld

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  1. Alejandra Barrera
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  2. Alfredo Weitzenfeld
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Correspondence to Alejandra Barrera.

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This research was partially supported by collaboration projects UC MEXUS CONACYT (ITAM–UCSC), LAFMI CONACYT (ITAM–ISC), NSF CONACYT (ITAM–UCI) under grant #42440 and “Asociación Mexicana de Cultura, S. A.”

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Barrera, A., Weitzenfeld, A. Biologically-inspired robot spatial cognition based on rat neurophysiological studies. Auton Robot 25, 147–169 (2008). https://doi.org/10.1007/s10514-007-9074-3

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