Lessons on the Reality-Gap: Iterations between Virtual and Real Robots

DOI

説明

Due to approximations between the virtual and real world, the knowledge transfer from simulations to robots is problematic. As physical conditions are prone to unknown and stochastic noise sources, the predictability reduces. We use data experiments from 100 real robots to tune the parameters of a simulation, and later used this tuned simulator to improve the design of the previous robots and find the optimum robot. We compare the simulated and observed behavior of this robot, and discuss our results.

収録刊行物

キーワード

詳細情報 詳細情報について

  • CRID
    1390845713049557120
  • DOI
    10.5954/icarob.2018.gs6-5
  • ISSN
    21887829
  • 本文言語コード
    en
  • データソース種別
    • JaLC
    • Crossref
  • 抄録ライセンスフラグ
    使用不可

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