In this article, we propose a complete and robust system for the aggressive flight of autonomous quadrotors. The proposed system is built upon on the classical teach-and-repeat framework, which is widely adopted in infrastructure inspection, aerial transportation, and search-and-rescue. For these applications, a human's intention is essential for deciding the topological structure of the flight trajectory of the drone. However, poor teaching trajectories and changing environments prevent a simple teach-and-repeat system from being applied flexibly and robustly. In this article, instead of commanding the drone to precisely follow a teaching trajectory, we propose a method to automatically convert a human-piloted trajectory, which can be arbitrarily jerky, to a topologically equivalent one. The generated trajectory is guaranteed to be smooth, safe, and dynamically feasible, with a human preferable aggressiveness. Also, to avoid unmapped or moving obstacles during flights, a fast local perception method and a sliding-windowed replanning method are integrated into our system, to generate safe and dynamically feasible local trajectories onboard. We name our system as teach–repeat–replan. It can capture users’ intention of a flight mission, convert an arbitrarily jerky teaching path to a smooth repeating trajectory, and generate safe local replans to avoid unexpected collisions. The proposed planning system is integrated into a complete autonomous quadrotor with global and local perception and localization submodules. Our system is validated by performing aggressive flights in challenging indoor/outdoor environments. We release all components in our quadrotor system as open-source ros packages.

中文翻译：

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Teach-Repeat-Replan：一个完整​​而强大的复杂环境下侵略性飞行系统

在本文中，我们为自主四旋翼飞行器的激进飞行提出了一个完整而强大的系统。所提出的系统建立在经典的教学和重复框架之上，该框架广泛用于基础设施检查、航空运输和搜救。对于这些应用，人类的意图对于决定无人机飞行轨迹的拓扑结构至关重要。然而，糟糕的教学轨迹和不断变化的环境阻碍了简单的教学和重复系统的灵活和稳健的应用。在本文中，我们不是命令无人机精确遵循教学轨迹，而是提出了一种方法，可以将人类驾驶的轨迹（可以任意抖动）自动转换为拓扑等效的轨迹。保证生成的轨迹是平滑的，安全，动态可行，具有人类可取的攻击性。此外，为了在飞行过程中避免未映射或移动的障碍物，我们的系统中集成了快速局部感知方法和滑动窗口重新规划方法，以在机上生成安全且动态可行的局部轨迹。我们将我们的系统命名为教学-重复-重新计划。它可以捕捉用户的飞行任务意图，将任意生涩的教学路径转换为平滑的重复轨迹，并生成安全的局部重新计划以避免意外碰撞。拟议的规划系统集成到一个完整的自主四旋翼飞行器中，具有全局和局部感知和定位子模块。我们的系统通过在具有挑战性的室内/室外环境中执行激进的飞行而得到验证。