Embodied Evolution for Collective Indoor Surveillance and Location

  • Pedro Trueba
  • Abraham Prieto
  • Francisco Bellas
  • Richard J. Duro
Conference paper

DOI: 10.1007/978-3-319-18833-1_15

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9108)
Cite this paper as:
Trueba P., Prieto A., Bellas F., Duro R.J. (2015) Embodied Evolution for Collective Indoor Surveillance and Location. In: Ferrández Vicente J., Álvarez-Sánchez J., de la Paz López F., Toledo-Moreo F., Adeli H. (eds) Bioinspired Computation in Artificial Systems. IWINAC 2015. Lecture Notes in Computer Science, vol 9108. Springer, Cham

Abstract

This work is devoted with the application of a canonical Embodied Evolution algorithm in a collective task in which a fleet of Micro Aerial Vehicles (MAVs) have to survey an indoor scenario. The MAVs need to locate themselves to keep track of their trajectories and to share this information with other robots. This localization is performed using the IMU, artificial landmarks that can be sensed using the onboard camera and the position of other MAVs in sight. The accuracy in the decentralized location of each MAV has been included as a part of the problem to solve. Therefore, the collective control system is in charge of organizing the MAVs in the scenario in order to increase the accuracy of the fleet location, and consequently, the speed at which a new point of interest is reached.

Keywords

Embodied Evolution Indoor Navigation Collective Tasks 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Pedro Trueba
    • 1
  • Abraham Prieto
    • 1
  • Francisco Bellas
    • 1
  • Richard J. Duro
    • 1
  1. 1.Integrated Group for Engineering ResearchUniversidade da CoruñaFerrolSpain

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