A Study on Path Planning for Autonomous Drones Considering Wind Risk

Abstract

In recent years, the use of drones has been advancing in various fields. In particular, attention is focused on autonomous drones that do not require a driver. However, autonomous drones need to use external information acquired by sensors to control flight so that the drone does not crash or become incapable of performing missions. In drones, it is important to consider the effects of wind-induced attitude changes, especially crashes, as well as preventing approach and collision with structures. However, as far as the author knows, path planning considering the influence of wind has not been announced so far. Therefore, we propose a method for path planning that avoids windy areas that have a large effect on drones. In this study, it is assumed that the drone can measure the current position and the wind direction and speed at that point. Based on that information, Model Predictive Control (MPC) performs path planning that predicts the wind condition around the drone and avoids windy areas. In this paper, we explain the wind prediction model and the setting of wind constraints for MPC. We also conducted an autonomous flight simulation in a windy environment to verify the effectiveness of the proposed method.