反復δ空間を用いたUAV動的軌道の二段階計画
Two-step Planning of Dynamic UAV Trajectories using Iterative $\delta$-Spaces
低次元経路の周辺だけでなく複数の準最適経路の和集合からなるδ空間を導入し、時間制約下でも局所解に陥りにくいUAV軌道を生成するanytimeアルゴリズムを提案した。
著者: Sebastian Schräder, Daniel Schleich, Sven Behnke
分類: cs.RO
原文アブストラクト
UAV trajectory planning is often done in a two-step approach, where a low-dimensional path is refined to a dynamic trajectory. The resulting trajectories are only locally optimal, however. On the other hand, direct planning in higher-dimensional state spaces generates globally optimal solutions but is time-consuming and thus infeasible for time-constrained applications. To address this issue, we propose $\delta$-Spaces, a pruned high-dimensional state space representation for trajectory refinement. It does not only contain the area around a single lower-dimensional path but consists of the union of multiple near-optimal paths. Thus, it is less prone to local minima. Furthermore, we propose an anytime algorithm using $\delta$-Spaces of increasing sizes. We compare our method against state-of-the-art search-based trajectory planning methods and evaluate it in 2D and 3D environments to generate second-order and third-order UAV trajectories.
