構造進化型人工神経回路網によるSwarm Roboticsのための適応的協調行動の生成

• 大倉 和博

  広島大学大学院工学研究院

• 保田 俊行

  広島大学大学院工学研究院

• 松村 嘉之

  信州大学繊維学部

書誌事項

タイトル別名

• Coordinating Adaptive Behavior for Swarm Robotics Based on Topology and Weight Evolving Artificial Neural Networks

抄録

Swarm robotics is the research field of multi-robot systems which consist of many homogeneous autonomous robots without any type of global controllers. Generally, since a task given to this system can not be achieved by a single autonomous robot, emergent cooperative behavior is expected in a robot swarm by a certain mechanism through the interactions among the robots or with an environment. In this paper, an evolutionary robotics approach, i.e., the method that the robot controllers are designed by evolutionary algorithms with artificial neural networks, is applied. Among many approaches to evolving artificial neural networks, two approaches, NEAT and MBEANN, are adopted for computer simulations. Although a conventional neural network evolves only synaptic weights with the condition of a fixed topology, NEAT and MBEANN evolve not only their synaptic weights but also their topologies. As a benchmark of swarm robotics, cooperative package pushing problems by ten autonomous robots are conducted to examine their performance. The emerged behavioral characteristics are discussed.

収録刊行物

• 日本機械学会論文集Ｃ編

  日本機械学会論文集Ｃ編 77 (775), 966-979, 2011

  一般社団法人 日本機械学会

キーワード

• Multi-Agent
• Distributed Coordination
• Neural Network
• Swarm Robotics
• Cooperative Package Pushing Task

詳細情報

• CRID: 1390001206386823040
• NII論文ID: 130000873805
• DOI: 10.1299/kikaic.77.966
• ISSN: 18848354
• ISSN: 03875024
• Web Site: http://www.jstage.jst.go.jp/article/kikaic/77/775/77_775_966/_pdf
• データソース種別:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可