狭環境におけるアフィン変形ガイダンスを用いた機数適応型フォーメーション飛行計画
Number Adaptive Formation Flight Planning via Affine Deformable Guidance in Narrow Environments
ドローン群の機数が変化しても狭い環境でフォーメーションを維持できるよう、変形可能な仮想構造(DVS)をアフィン変換で誘導する計画手法を提案し、シミュレーションと実機実験で有効性を示した。
詳しい要約
1. どんなもの？
2. 先行研究と比べてどこがすごい？
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著者: Yuan Zhou, Jialiang Hou, Guangtong Xu, Fei Gao
分類: cs.RO
原文アブストラクト
Formation maintenance with varying number of drones in narrow environments hinders the convergence of planning to the desired configurations. To address this challenge, this paper proposes a formation planning method guided by Deformable Virtual Structures (DVS) with continuous spatiotemporal transformation. Firstly, to satisfy swarm safety distance and preserve formation shape filling integrity for irregular formation geometries, we employ Lloyd algorithm for uniform $\underline{PA}$rtitioning and Hungarian algorithm for $\underline{AS}$signment (PAAS) in DVS. Subsequently, a spatiotemporal trajectory involving DVS is planned using primitive-based path search and nonlinear trajectory optimization. The DVS trajectory achieves adaptive transitions with respect to a varying number of drones while ensuring adaptability to narrow environments through affine transformation. Finally, each agent conducts distributed trajectory planning guided by desired spatiotemporal positions within the DVS, while incorporating collision avoidance and dynamic feasibility requirements. Our method enables up to 15\% of swarm numbers to join or leave in cluttered environments while rapidly restoring the desired formation shape in simulation. Compared to cutting-edge formation planning method, we demonstrate rapid formation recovery capacity and environmental adaptability. Real-world experiments validate the effectiveness and resilience of our formation planning method.
