Bat Algorithm for Coordinated Exploration in Swarm Robotics

  • Patricia Suárez
  • Andrés IglesiasEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 514)


Bat algorithm is a powerful bio-inspired swarm intelligence method with remarkable applications in several industrial and scientific domains. However, to the best of authors’ knowledge, this algorithm has not been applied so far to the exciting field of swarm robotics. This paper describes the first physical and computational implementation of the bat algorithm to a swarm of simple robotic units. The swarm consists of a set of identical wheeled robots equipped with simple yet powerful components that replicate the most important features of the bat algorithm by either hardware or software. The swarm has been applied to the problem of coordinated exploration, where the individual self-organizing robots generate an intelligent collective behavior emerging from the interactions between the robots and with the environment. A computational and real-world experiment has been carried out to check the feasibility and performance of this approach. Our experimental results show that the bat algorithm is extremely well suited for this task, actually leading to surprisingly intelligent behavioral patterns much better than expected.


Swarm computation Swarm robotics Coordinated exploration Bat algorithm Collective behavior 



This research has been kindly supported by the Computer Science National Program of the Spanish Ministry of Economy and Competitiveness, Project Ref. #TIN2012-30768, Toho University, and the University of Cantabria.


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© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Faculty of SciencesUniversity of CantabriaSantanderSpain
  2. 2.Department of Information Science, Faculty of SciencesToho UniversityFunabashiJapan
  3. 3.Department of Applied Mathematics and Computational SciencesUniversity of CantabriaSantanderSpain

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