マルチロータ飛行のためのサンプリングベース運動学的計画への高速領域最適化の統合
Integrating Fast Regional Optimization into Sampling-based Kinodynamic Planning for Multirotor Flight
局所環境情報を活用する高速領域最適化器を提案し、グローバルなサンプリング計画に統合することで、狭通路などの難所を含む環境での成功率向上と計画時間短縮を実現した。
著者: Hongkai Ye, Tianyu Liu, Chao Xu, Fei Gao
分類: cs.RO
原文アブストラクト
For real-time multirotor kinodynamic motion planning, the efficiency of sampling-based methods is usually hindered by difficult-to-sample homotopy classes like narrow passages. In this paper, we address this issue by a hybrid scheme. We firstly propose a fast regional optimizer exploiting the information of local environments and then integrate it into a global sampling process to ensure faster convergence. The incorporation of local optimization on different sampling-based methods shows significantly improved success rates and less planning time in various types of challenging environments. We also present a refinement module that fully investigates the resulting trajectory of the global sampling and greatly improves its smoothness with negligible computation effort. Benchmark results illustrate that compared to the state-of-the-art ones, our proposed method can better exploit a previous trajectory. The planning methods are applied to generate trajectories for a simulated quadrotor system, and its capability is validated in real-time applications.
