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A Comparison of Sampling Strategies for Parameter Estimation of a Robot Simulator

  • Conference paper
Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7628))

Abstract

Methods for dealing with the problem of the “reality gap” in evolutionary robotics are described. The focus is on simulator tuning, in which simulator parameters are adjusted in order to more accurately model reality. We investigate sample selection, which is the method of choosing the robot controllers, evaluated in reality, that guide simulator tuning. Six strategies for sample selection are compared on a robot locomotion task. It is found that strategies that select samples that show high fitness in simulation greatly outperform those that do not. One such strategy, which selects the sample that is the expected fittest as well as the most informative (in the sense of producing the most disagreement between potential simulators), results in the creation of a nearly optimal simulator in the first iteration of the simulator tuning algorithm.

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© 2012 Springer-Verlag Berlin Heidelberg

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Klaus, G., Glette, K., Tørresen, J. (2012). A Comparison of Sampling Strategies for Parameter Estimation of a Robot Simulator. In: Noda, I., Ando, N., Brugali, D., Kuffner, J.J. (eds) Simulation, Modeling, and Programming for Autonomous Robots. SIMPAR 2012. Lecture Notes in Computer Science(), vol 7628. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34327-8_18

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  • DOI: https://doi.org/10.1007/978-3-642-34327-8_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34326-1

  • Online ISBN: 978-3-642-34327-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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