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Synthesizing Physically-Realistic Environmental Models from Robot Exploration

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Book cover Advances in Artificial Life (ECAL 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4648))

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Abstract

In previous work [4] a framework was demonstrated that allows an autonomous robot to automatically synthesize physically-realistic models of its own body. Here it is demonstrated how the same approach can be applied to empower a robot to synthesize physically-realistic models of its surroundings. Robots which build numerical or other non-physical models of their environments are limited in the kinds of predictions they can make about the repercussions of future actions. In this paper it is shown that a robot equipped with a self-made, physically-realistic model can extrapolate: a slow-moving robot consistently predicts the much faster top speed at which it can safely drive across a terrain.

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Authors and Affiliations

  1. Department of Computer Science, University of Vermont, 33 Colchester Ave., Burlington, VT 05405,  

    Josh Bongard

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  1. Josh Bongard
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Editor information

Fernando Almeida e Costa Luis Mateus Rocha Ernesto Costa Inman Harvey António Coutinho

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© 2007 Springer-Verlag Berlin Heidelberg

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Bongard, J. (2007). Synthesizing Physically-Realistic Environmental Models from Robot Exploration. In: Almeida e Costa, F., Rocha, L.M., Costa, E., Harvey, I., Coutinho, A. (eds) Advances in Artificial Life. ECAL 2007. Lecture Notes in Computer Science(), vol 4648. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74913-4_81

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  • DOI: https://doi.org/10.1007/978-3-540-74913-4_81

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74912-7

  • Online ISBN: 978-3-540-74913-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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