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Intelligent robot navigation using view sequences and a sparse distributed memory

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Paladyn

Abstract

Different approaches have been tried to navigate robots, including those based on visual memories. The Sparse Distributed Memory (SDM) is a kind of associative memory based on the properties of high dimensional binary spaces. It exhibits characteristics such as tolerance to noise and incomplete data, ability to work with sequences and the possibility of one-shot learning. Those characteristics make it appealing to use for robot navigation. The approach presented in this work was to navigate a robot using sequences of visual memories stored into a SDM. The robot makes intelligent decisions, such as selecting only relevant images to store during path learning, adjusting memory parameters to the level of noise and inferring new paths from learnt trajectories. The method of encoding the information may influence the tolerance of the SDM to noise and saturation. The present paper reports novel results of the limits of the model under different typical navigation problems. An algorithm to build a topological map of the environment based on the visual memories is also described.

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Authors and Affiliations

  1. Polytechnic Institute of Coimbra, ESTGOH, Coimbra, Portugal

    Mateus Mendes

  2. Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal

    A. Paulo Coimbra & Manuel M. Crisóstomo

Authors
  1. Mateus Mendes
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  2. A. Paulo Coimbra
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  3. Manuel M. Crisóstomo
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Corresponding author

Correspondence to Mateus Mendes.

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Mendes, M., Paulo Coimbra, A. & Crisóstomo, M.M. Intelligent robot navigation using view sequences and a sparse distributed memory. Paladyn 1, 240–254 (2010). https://doi.org/10.2478/s13230-011-0010-z

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  • DOI: https://doi.org/10.2478/s13230-011-0010-z

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