Frontiers reaches 6.4 on Journal Impact Factors

Review ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Robot. AI | doi: 10.3389/frobt.2018.00012

Embodied Evolution in Collective Robotics: A Review

  • 1Institute of Intelligent Systems and Robotics, Université Pierre et Marie Curie, France
  • 2Department of Computer Science,, VU University Amsterdam, Netherlands
  • 3Integrated Group for Engineering Research, University of A Coruña, Spain

This paper provides an overview of evolutionary robotics techniques applied to on-line distributed evolution for robot collectives - namely, embodied evolution. It provides a definition of embodied evolution as well as a thorough description of the underlying concepts and mechanisms. The paper also presents a comprehensive summary of research published in the field since its inception around the year 2000, providing various perspectives to identify the major trends. In particular, we identify a shift from considering embodied evolution as a parallel search method within small robot collectives (fewer than 10 robots) to embodied evolution as an on-line distributed learning method for designing collective behaviours in swarm-like collectives. The paper concludes with a discussion of applications and open questions, providing a milestone for past and an inspiration for future research.

Keywords: embodied evolution, On-line distributed evolution, collective robotics, Evolutionary Robotics, Collective Adaptive Systems

Received: 30 Nov 2017; Accepted: 29 Jan 2018.

Edited by:

Elio Tuci, Middlesex University, United Kingdom

Reviewed by:

Yara Khaluf, Ghent University, Belgium
Aparajit Narayan, Aberystwyth University, United Kingdom  

Copyright: © 2018 Bredeche, Haasdijk and Prieto. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Nicolas Bredeche, BREDECHE., Université Pierre et Marie Curie, Institute of Intelligent Systems and Robotics, Pyramide ISIR T55-56, 4 place Jussieu, BP 173, Paris, 75005, France, nicolas.bredeche@upmc.fr