制御バリア機能とコンセンサス理論に基づく異質なAUVの協力的カバーコントロール
Fengxiang Mao1, Dongsong Zhang1, Liang Xu1
1School of Big Data and Artificial Intelligence, Xinyang College, Xinyang 464000, China.
Sensors (Basel, Switzerland)
|February 13, 2026
まとめ
この研究は,安全性を確保しながら最適なカバーを達成するために,異質な自律型水中車両 (AUV) の群れのための新しい制御フレームワークを提示しています. この方法は,制御バリア機能とコンセンサス理論を統合して,複雑な環境で堅牢なナビゲーションとタスクの完了を実現します.
科学分野:
- ロボット工学と制御システム
- マルチエージェントシステム
- 自動ナビゲーション 自動ナビゲーション
背景:
- 複合的な環境における自律型水中車両 (AUV) の群れにとって,協力的なカバーコントロールは極めて重要です.
- AUVの能力とセンシング範囲の異質性は,大きな課題を提示します.
- 衝突回避とダイナミックな制約の確保は,カバーとともに重要な問題です.
研究 の 目的:
- 異質なAUV群の階層的な制御フレームワークを開発する.
- 衝突回避を保証し,AUVのダイナミクスを尊重しながら,最適なエリアカバーを達成するために.
- 協力的な水中ミッションの堅実性と効率性を高めること.
主な方法:
- 協力的なカバーモデリングのための修正されたヴォロノイ分割.
- ワークロードのバランスと自己組織化されたカバーのためのコンセンサス理論.
- 制御バリア機能 (CBF),ゼロリングCBF (ZCBF) とハイオーダーCBF (HOCBF) を含む安全保証のための制御バリア機能.
- カバレッジ制御と安全制約を統合するための二次プログラミング (QP).
主要な成果:
- 提案された枠組みは,安全なセットの安定性と前向きの不変性を保証します.
- 協同組合のカバータスクの収束が実証された.
- AUVの衝突回避と速度制限を成功裏に統一しました.
- 障害のある複雑な環境での有効性と強度が検証されています.
結論:
- 階層的な制御フレームワークは,最適のカバーと安全性を確保するために,異質なAUV群を効果的に管理します.
- CBFとコンセンサス理論の統合は,複雑な水中ミッションに強力なソリューションを提供します.
- この方法は,自律的なシステムの安全性に欠かせない層を最小限侵入的に提供します.
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