緩やかに結合された部品の統計力学に基づく粒子ロボット
Shuguang Li1,2, Richa Batra3, David Brown4
1Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA. lisg@csail.mit.edu.
Nature
|March 22, 2019
まとめ
この研究は,統計力学を用いた無形ロボットシステムを導入します. これらのロボットは 部品の故障にも関わらず 頑丈な動きと機能のために シンプルで緩やかに結合された多くの粒子を利用します
科学分野:
- ロボット
- 統計的メカニズム
- 複雑なシステム
背景:
- 生物学的なシステムは 明確な制御を必要とする 現在のロボットとは異なり 頑丈な行動のための ストカスティックな構成要素を使用します
- 従来のロボットは 部品の"つが故障すると 完全に故障します
- 既存のロボットシステムは 通常は単体またはモジュラーで 調整され 個別的に制御される部品です
研究 の 目的:
- 統計力学の現象によって制御される 新しいロボットシステムを実証する
- 頑丈で複雑なロボットシステムの可能性を 探求するためです
- 個別化されていない粒子のシステムにおける運動と刺激反応を調査する.
主な方法:
- 独立した移動や識別ができない多数の緩い結合した"粒子"を組み込む.
- 粒子の均一な体積振動を利用し,全局信号によって相調節されます.
- 物理ロボット (最大24粒) とシミュレートロボット (最大10万粒) のテスト
主要な成果:
- 頑丈な運動,物体輸送,そして無形ロボットシステムでの光学を証明した.
- 20%の粒子の故障にもかかわらず 持続的な動きを達成しました
- 低レベル粒子のストキャスティック運動から生じる 決定的な高レベルの行動を示した.
結論:
- ストキャスティックシステムは 複雑で頑丈なロボットを作る 新しいパラダイムを提供します
- 大規模な無形ロボットシステムは 決定的行動を示すことができる.
- このアプローチは,従来の明示的に制御されたロボットデザインの代替案です.
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