進化型スワームロボティクスにおける協調採餌問題のGPUへの実装

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2014/09/01

タイトル(英語): GPU Implementation of Food-Foraging Problem for Evolutionary Swarm Robotics Systems

著者名: 島谷　直規（広島大学大学院工学研究科），保田　俊行（広島大学大学院工学研究科），大倉　和博（広島大学大学院工学研究科），松村　嘉之（信州大学繊維学部）

著者名(英語): Naoki Shimatani (Graduate School of Engineering, Hiroshima University), Toshiyuki Yasuda (Graduate School of Engineering, Hiroshima University), Kazuhiro Ohkura (Graduate School of Engineering, Hiroshima University), Yoshiyuki Matsumura (Faculty of Textile Science and Technology, Shinshu University)

キーワード: スワームロボティクス，進化ロボティクス，GPUコンピューティング　　Swarm Robotics，Evolutionary Robotics，GPU Computing

要約(英語): Evolutionary swarm robotics (ESR) is an artificial evolution approach to generating meaningful swarm behavior in multi-robot systems which typically consist of many homogenous autonomous robots in which the same robot controllers designed with evolving artificial neural networks are employed. Historically speaking, this approach has been thought to be a promising approach for swarm robotics systems (SRS), because the swarm behavior is an emergent phenomenon caused by many local interactions among autonomous robots and it is very hard to give a program to each robot for appropriate swarm behavior in advance. However, its realization is considered to be impractical even for a simulated SRS because the artificial evolution requires a very large computational cost. In this paper, in order to overcome this computational cost problem, a novel implementation method, i.e., the parallel problem solving using graphics processing units (GPUs) and OpenMP on a multi-core CPU, is introduced. The efficiency of the proposed method is demonstrated with the food-foraging problem with an evolving SRS.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.134 No.9 （2014） 特集Ⅰ：制御系設計における適応・学習・同定・モデリングの新展開　特集Ⅱ：インテリジェント・システム

本誌掲載ページ: 1355-1364 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/134/9/134_1355/_article/-char/ja/