We use graph signal sampling and recovery techniques to plan routes for autonomous aerial vehicles. We propose a novel method that plans an energy-efficient flight trajectory by considering the influence of wind. We model the weather stations as nodes on a graph and model wind velocity at each station as a graph signal. We observe that the wind velocities at two close stations are similar, that is, the graph signal of wind velocities is smooth. By taking advantages of the smoothness, we only query a small fraction of it and recover the rest by using a novel graph signal recovery algorithm, which solves an optimization problem. To validate the effectiveness of the proposed method, we first demonstrate the necessity to take wind into account when planning route for autonomous aerial vehicles, and then show that the proposed method produces a reliable and energy-efficient route.
['Tianxi Ji', 'Siheng Chen', 'Rohan Varma', 'Jelena Kovacevic']
Energy-efficient route planning for autonomous aerial vehicles based on graph signal recovery