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

• OHKURA Kazuhiro

  Graduate School of Engineering, Hiroshima University

• YASUDA Toshiyuki

  Graduate School of Engineering, Hiroshima University

• MATSUMURA Yoshiyuki

  信州大学繊維学部

Bibliographic Information

Other Title

• 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

Abstract

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.

Journal

• TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C

  TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C 77 (775), 966-979, 2011

  The Japan Society of Mechanical Engineers

Keywords

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

Details

• CRID: 1390001206386823040
• NII Article 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
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed