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Evolving controllers for high-level applications on a service robot: a case study with exhibition visitor flow control

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Abstract

We investigate the application of simulation-based genetic programming to evolve controllers that perform high-level tasks on a service robot. As a case study, we synthesize a controller for a guide robot that manages the visitor traffic flow in an exhibition space in order to maximize the enjoyment of the visitors. We used genetic programming in a low-fidelity simulation to evolve a controller for this task, which was then transferred to a service robot. An experimental evaluation of the evolved controller in both simulation and on the actual service robot shows that it performs well compared to hand-coded heuristics, and performs comparably to a human operator.

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Notes

  1. The entire simulation system, including some unit test code, as well as a simple GUI for displaying simulation runs and setting some control parameters, is only 770 lines of Common Lisp code, and required approximately 25 h to implement, so this is clearly not an elaborate simulator.

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Authors and Affiliations

  1. The University of Tokyo, Tokyo, Japan

    Alex Fukunaga, Hideru Hiruma, Kazuki Komiya & Hitoshi Iba

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  1. Alex Fukunaga
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  2. Hideru Hiruma
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  3. Kazuki Komiya
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  4. Hitoshi Iba
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Correspondence to Alex Fukunaga.

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Fukunaga, A., Hiruma, H., Komiya, K. et al. Evolving controllers for high-level applications on a service robot: a case study with exhibition visitor flow control. Genet Program Evolvable Mach 13, 239–263 (2012). https://doi.org/10.1007/s10710-011-9152-3

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  • DOI: https://doi.org/10.1007/s10710-011-9152-3

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