Research Output

The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World

  The long term vision of the Autonomous Robot Evolution (ARE) project is to create an ecosystem of both virtual and physical robots with evolving brains and bodies. One of the major challenges for such a vision is the need to construct many unique individuals without prior knowledge of what designs evolution will produce. To this end, an autonomous robot fabrication system for evolutionary robotics, the Robot Fabricator, is introduced in this paper. Evolutionary algorithms can create robot designs without direct human interaction ; the Robot Fabricator will extend this to create physical copies of these designs (phenotypes) without direct human interaction. The Robot Fabricator will receive genomes and produce populations of physical individuals that can then be evaluated, allowing this to form part of the evolutionary loop, so robotic evolution is not confined to simulation and the reality gap is minimised. In order to allow the production of robot bodies with the widest variety of shapes and functional parts, individuals will be produced through 3D printing, with prefabricated actuators and sensors autonomously attached in the positions determined by evolution. This paper presents details of the proposed physical system, including a proof-of-concept demonstrator, and discusses the importance of considering the physical manufacture for evolutionary robotics.

  • Date:

    15 July 2019

  • Publication Status:

    Published

  • DOI:

    10.1162/isal_a_00147

  • Library of Congress:

    TJ Mechanical engineering and machinery

  • Dewey Decimal Classification:

    006.3 Artificial intelligence

  • Funders:

    Engineering and Physical Sciences Research Council

Citation

Hale, M. F., Buchanan, E., Winfield, A. F., Timmis, J., Hart, E., Eiben, A. E., …Tyrrell, A. M. (2019). The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World. In ALIFE 2019: The 2019 Conference on Artificial Life, 95-102. https://doi.org/10.1162/isal_a_00147

Authors

Keywords

Evolutionary Robotics

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