论文标题
使用无需能源的无人机覆盖环境
Coverage of an Environment Using Energy-Constrained Unmanned Aerial Vehicles
论文作者
论文摘要
我们研究了使用电池容量有限的无人机（UAV）覆盖环境的问题。我们考虑一种场景，无人机可以降落在无人接地车辆（UGV）上并为车载电池充电。 UGV还可以在将无人机运送到下一个起飞地点时为无人机充电。我们提出了一种算法来解决该区域覆盖问题的新变体，该算法考虑了这种共生无人机和UGV系统。该输入由一组布斯特犬细胞组成 - 矩形带，其宽度等于无人机上传感器的视野。目的是为无人机和UGV找到一种协调的策略，该策略在最短的时间内访问并覆盖所有单元，同时最佳地找到可充电，在哪里充电以及何时为电池充电。这包括访问和覆盖所有细胞的飞行时间，充电时间以及起飞和着陆时间。我们展示了如何将这个问题减少到已知的NP问题，广义旅行销售人员问题（GTSP）。鉴于最佳的GTSP求解器，我们的方法找到了无人机和UGV的最佳覆盖路径。我们的公式模型多旋转无人机以及可以在固定翼和垂直起飞和着陆模式下运行的混合无人机。我们通过模拟和概念验证实验评估算法。
We study the problem of covering an environment using an Unmanned Aerial Vehicle (UAV) with limited battery capacity. We consider a scenario where the UAV can land on an Unmanned Ground Vehicle (UGV) and recharge the onboard battery. The UGV can also recharge the UAV while transporting the UAV to the next take-off site. We present an algorithm to solve a new variant of the area coverage problem that takes into account this symbiotic UAV and UGV system. The input consists of a set of boustrophedon cells -- rectangular strips whose width is equal to the field-of-view of the sensor on the UAV. The goal is to find a coordinated strategy for the UAV and UGV that visits and covers all cells in minimum time, while optimally finding how much to recharge, where to recharge, and when to recharge the battery. This includes flight time for visiting and covering all cells, recharging time, as well as the take-off and landing times. We show how to reduce this problem to a known NP-hard problem, Generalized Traveling Salesperson Problem (GTSP). Given an optimal GTSP solver, our approach finds the optimal coverage paths for the UAV and UGV. Our formulation models multi-rotor UAVs as well as hybrid UAVs that can operate in fixed-wing and Vertical Take-off and Landing modes. We evaluate our algorithm through simulations and proof-of-concept experiments.
