RoboCup 2019 アダルトサイズ優勝チーム NimbRo：深層学習知覚・歩行中キック・押され復帰・チームプレー
RoboCup 2019 AdultSize Winner NimbRo: Deep Learning Perception, In-Walk Kick, Push Recovery, and Team Play Capabilities
ヒューマノイドサッカー大会RoboCup 2019で優勝したNimbRoの最新技術（深層学習による視覚認識、歩きながらのキック、踏み出しによる押され復帰、チーム連携戦略）を報告する論文。
著者: Diego Rodriguez, Hafez Farazi, Grzegorz Ficht, Dmytro Pavlichenko, Andre Brandenburger, Mojtaba Hosseini, Oleg Kosenko, Michael Schreiber, Marcel Missura, Sven Behnke
分類: cs.RO
原文アブストラクト
Individual and team capabilities are challenged every year by rule changes and the increasing performance of the soccer teams at RoboCup Humanoid League. For RoboCup 2019 in the AdultSize class, the number of players (2 vs. 2 games) and the field dimensions were increased, which demanded for team coordination and robust visual perception and localization modules. In this paper, we present the latest developments that lead team NimbRo to win the soccer tournament, drop-in games, technical challenges and the Best Humanoid Award of the RoboCup Humanoid League 2019 in Sydney. These developments include a deep learning vision system, in-walk kicks, step-based push-recovery, and team play strategies.
