An Experiment in Automatic Design of Robot Swarms AutoMoDe-Vanilla, EvoStick, and Human Experts

We present an experiment in automatic design of robot swarms. For the first time in the swarm robotics literature, we perform an objective comparison of multiple design methods: we compare swarms designed by two automatic methods-AutoMoDe-Vanilla and EvoStick-with swarms manually designed by human experts. AutoMoDe-Vanilla and EvoStick have been previously published and tested on two tasks. To evaluate their generality, in this paper we test them without any modification on five new tasks. Besides confirming that AutoMoDe-Vanilla is effective, our results provide new insight into the design of robot swarms. In particular, our results indicate that, at least under the adopted experimental protocol, not only does automatic design suffer from the reality gap, but also manual design. The results also show that both manual and automatic methods benefit from bias injection. In this work, bias injection consists in restricting the design search space to the combinations of pre-existing modules. The results indicate that bias injection helps to overcome the reality gap, yielding better performing robot swarms.

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Francesca, Gianpiero
Brambilla, Manuele
Brutschy, Arne
Garattoni, Lorenzo
Miletitch, Roman
Podevijn, Gaetan
Reina, Andreagiovanni
Soleymani, Touraj
Salvaro, Mattia
Pinciroli, Carlo
Trianni, Vito
Birattari, Mauro
Springer, Berlin , Germania
ANTS 2014: Ninth International Conference on Swarm Intelligence, pp. 25–37, 2014
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