Collision-free path planning is an essential requirement for autonomous exploration in unknown environments, especially when operating in confined spaces or near obstacles. This study presents an autonomous exploration technique using a small drone. A local end-point selection method is designed using LiDAR range measurement and then generates the path from the current position to the selected end-point. The generated path shows the consistent collision-free path in real-time by adopting the Euclidean signed distance field-based grid-search method. The simulation results consistently showed the safety, and reliability of the proposed path-planning method. Real-world experiments are conducted in three different mines, demonstrating successful autonomous exploration flight in environments with various structural conditions. The results showed the high capability of the proposed flight autonomy framework for lightweight aerial-robot systems. Besides, our drone performs an autonomous mission during our entry at the Tunnel Circuit competition (Phase 1) of the DARPA Subterranean Challenge.
翻译:无碰撞路径规划是在未知环境中进行自主探索的基本要求,特别是在封闭空间或近距离障碍下作业时。本研究展示了使用小型无人驾驶飞机的自主探索技术。当地端点选择方法使用LiDAR射程测量设计,然后生成了从当前位置到选定终点的路径。生成路径通过采用欧clidean签署的远距离实地网格搜索方法,显示了实时的连续无碰撞路径。模拟结果始终显示拟议路径规划方法的安全性和可靠性。现实世界实验在三个不同的矿区进行,展示了在结构条件不同的环境中成功自主探索飞行的情况。结果显示,拟议的轻量空中机器人系统飞行自主框架具有很高的能力。此外,我们的无人驾驶飞机在进入DARPA Subterranane Challenge的隧道巡回竞赛(第1阶段)期间执行自主任务。