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A hierarchical cognitive architecture for robot exploration and recognition of object shape is presented. This cognitive architecture proposes the combination of multiple robot behaviours based on (1) Evolutionary, (2) Fuzzy Logic and (3) Bayesian approaches. First, the Evolutionary approach allows a swarm of robots to locate and reach an object for exploration. Second, Fuzzy Logic is used to control the exploration of the object shape. Third, the Bayesian approach allows the robot to detect the orientation of the walls of the object being explored. Once the exploration process finishes, the swarm of robots determine whether the object has a rectangular or circular shape. This work is validated in a simulated environment and MATLAB using a swarm of E-puck robots. Overall, the experiments demonstrate that simple robots are capable of performing complex tasks through the combination of simple collective behaviours while learning from the interaction with the environment.

Original languageEnglish
Title of host publicationBiomimetic and Biohybrid Systems. Living Machines 2019
EditorsUriel Martinez-Hernandez, Vasiliki Vouloutsi, Anna Mura, Michael Mangan, Tony J. Prescott, Minoru Asada, Paul F.M.J. Verschure
Place of PublicationCham, Switzerland
PublisherSpringer Verlag
Number of pages5
ISBN (Print)9783030247409
Publication statusE-pub ahead of print - 6 Jul 2019
Event8th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2019 - Nara, Japan
Duration: 9 Jul 201912 Jul 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11556 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference8th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2019


  • Bayesian perception
  • Hierarchical control
  • Swarm robotics

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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