In this paper, we present an online planning-scheduling approach for battery-powered autonomous aerial robots. The approach consists of simultaneously planning a coverage path and scheduling onboard computational tasks. We further derive a novel variable coverage motion robust to airborne constraints and an empirically motivated energy model. The model includes the energy contribution of the schedule based on an automatic computational energy modeling tool. Our experiments show how an initial flight plan is adjusted online as a function of the available battery, accounting for uncertainty. Our approach remedies possible in-flight failure in case of unexpected battery drops, e.g., due to adverse atmospheric conditions, and increases the overall fault tolerance.

翻译：在本文中,我们介绍了电池动力自主航空机器人的在线规划安排方法,包括同时规划一个覆盖路径和船上计算任务的时间安排。我们进一步得出了一种对空气中限制具有活力的新变数覆盖运动和一种经验驱动的能源模型。模型包括基于自动计算能源模型工具的时间表的能源贡献。我们的实验表明,初始飞行计划是如何根据可用电池的功能在网上调整的,考虑到不确定性。我们的方法是在发生意外电池投落时(例如由于不利的大气条件)在飞行中发生故障时可能采取的补救方法,并增加了整体的过错容忍度。