部分的初期化によるParticle Swarm Optimizationの拡張（第2報，マルチロボットシステム問題における検証）

• 保田 俊行

  広島大学大学院工学研究院

• 大倉 和博

  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

• An Extension of Particle Swarm Optimization Based on Partial Initialization (The 2nd Report, Performance Evaluation on a Multi-Robot System Problem)

抄録

This paper investigates a particle swarm optimization (PSO) approach to a multi-robot system. PSO is known to be relatively implementable with ease, and efficient for solving various optimization problems. However, the inefficiency for large scaled multimodal problems has also been reported. In order to overcome this unwanted characteristics of PSO, we have been developing a noble method that performs the partial initialization in a small probability and demonstrating its basic effectiveness to benchmark functions. Further discussion on a real world problem is conducted in this paper. We tackle the control of autonomous mobile robots by PSO. Similar to typical methods of evolutionary robotics, artificial neural networks (ANN) is employed as a controller of each robot. PSO is utilized as a methodology for designing ANNs. To examine our approach, computer simulations are conducted using a cooperative box-pushing task. The results obtained are compared with a standard PSO results. It is found that our proposed approach outperforms a conventional one.

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 (777), 2084-2095, 2011

  一般社団法人 日本機械学会

キーワード

• Particle Swarm Optimization
• Multimodal Problem
• Global Search
• Local Search
• Partial Initialization
• Multi-Agent
• Autonomy
• Distributed Coordination

詳細情報

• CRID: 1390001206387035776
• NII論文ID: 130000873646
• DOI: 10.1299/kikaic.77.2084
• ISSN: 18848354
• ISSN: 03875024
• Web Site: http://www.jstage.jst.go.jp/article/kikaic/77/777/77_777_2084/_pdf
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  • KAKEN
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