トポロジカル経路と勾配最適化を統合した堅牢なUAVリアルタイム再計画
Robust Real-time UAV Replanning Using Guided Gradient-based Optimization and Topological Paths
局所解に陥りやすい勾配ベース軌道最適化を、3次元環境で複数の有用な経路を探索して各経路で独立に最適化するトポロジカル経路誘導により改善し、再計画成功率と最適性を高めた手法を提案。
著者: Boyu Zhou, Fei Gao, Jie Pan, Shaojie Shen
分類: cs.RO
原文アブストラクト
Gradient-based trajectory optimization (GTO) has gained wide popularity for quadrotor trajectory replanning. However, it suffers from local minima, which is not only fatal to safety but also unfavorable for smooth navigation. In this paper, we propose a replanning method based on GTO addressing this issue systematically. A path-guided optimization (PGO) approach is devised to tackle infeasible local minima, which improves the replanning success rate significantly. A topological path searching algorithm is developed to capture a collection of distinct useful paths in 3-D environments, each of which then guides an independent trajectory optimization. It activates a more comprehensive exploration of the solution space and output superior replanned trajectories. Benchmark evaluation shows that our method outplays state-of-the-art methods regarding replanning success rate and optimality. Challenging experiments of aggressive autonomous flight are presented to demonstrate the robustness of our method. We will release our implementation as an open-source package.
