陸空両用生物模倣ロボットのための改良型PPOに基づくグローバル経路計画
Weilai Jiang1,2, Jingwei Liu1,2, Wei Wang3
1The College of Artificial Intelligence and Robotics, Hunan University, Changsha 410082, China.
Biomimetics (Basel, Switzerland)
|January 27, 2026
まとめ
本研究では、陸空両用ロボットのための改良型近接方策最適化(IPPO)アルゴリズムを紹介します。強化されたフレームワークは、よりスムーズなモード遷移と複雑な環境でのより効率的な経路計画を可能にします。
科学分野:
- ロボット工学;人工知能;制御システム
背景:
- 両生類ロボットは、陸上モードと空中モード間の運動学的不連続性により、ナビゲーションの課題に直面します。;構造化されていない環境は、自律システムにとって重大な経路計画の困難をもたらします。
研究 の 目的:
- 陸空両用生物模倣ロボットのための堅牢なグローバル経路計画アルゴリズムを開発すること。;モード遷移中の意思決定を改善し、探索効率を高めること。
主な方法:
- 改良型近接方策最適化(IPPO)フレームワークの実装。;時間的依存性を捉えるためのゲート付き回帰ユニット(GRU)の統合。;安定したアクション生成のためのオルンシュタイン=ウーレンベック(OU)ノイズの利用。;特徴の優先順位付けのためのマルチヘッド自己注意機構の価値ネットワークへの組み込み。
主要な成果:
- 提案されたIPPOアルゴリズムは、標準的なPPOベースラインと比較して優れたパフォーマンスを示しました。;シミュレーションにおいて、より高い収束速度と改善された経路平滑性を達成しました。;複雑な両生類経路計画シナリオでより高い成功率を示しました。
結論:
- 強化されたIPPOフレームワークは、両生類ロボットの経路計画の課題を効果的に解決します。;GRUおよび自己注意機構の統合は、ナビゲーション能力を大幅に向上させます。;このアプローチは、挑戦的なマルチドメイン環境での自律運用に有望なソリューションを提供します。
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