用懒惰搜索提升无人机路径规划效率
Towards Efficient Motion Planning for UAVs: Lazy A* Search with Motion Primitives
- 引入懒惰搜索思想，延迟动态可行性验证
- 在保证轨迹动态可行的前提下大幅减少计算时间
- 适合资源受限的实时无人机路径规划场景
基于搜索的路径规划算法广泛应用于无人飞行器（UAV）。然而，在真实 UAV 上部署这些算法面临计算资源有限的挑战：算法在高维搜索空间中难以快速求解，且需大量时间确保轨迹具有动力学可行性。本文将懒惰搜索概念引入基于搜索的规划算法，解决 UAV 实时规划无碰撞且动力学可行轨迹的关键问题。实验表明，该懒惰搜索规划算法能高效找到最优轨迹，并显著提升计算效率。
原文摘要 · Abstract (English)
Search-based motion planning algorithms have been widely utilized for unmanned aerial vehicles (UAVs). However, deploying these algorithms on real UAVs faces challenges due to limited onboard computational resources. The algorithms struggle to find solutions in high-dimensional search spaces and require considerable time to ensure that the trajectories are dynamically feasible. This paper incorporates the lazy search concept into search-based planning algorithms to address the critical issue of real-time planning for collision-free and dynamically feasible trajectories on UAVs. We demonstrate that the lazy search motion planning algorithm can efficiently find optimal trajectories and significantly improve computational efficiency.
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