Optimal Path Planning for Autonomous Spraying UAS framework in Precision Agriculture

This paper presents a novel guidance and control strategy for multirotor Unmanned Aerial Systems (UASs) which aims to provide an autonomous and safe mission in precision agriculture applications. In the last few years, the research in this field has always improved thanks to the advent of new technologies and with the launch of the first smart farms. Precision aerial spraying of Plant Protection Products (PPP) in vineyards is the focus of this work, highlighting several advantages in terms of quality management, time and cost. In particular, we propose a combination of a Traveling Salesman Problem (TSP) solver with the well-know Theta* algorithm to investigate optimal UAS trajectories in order to visit a specific number of plants that require intervention. The final goal is to demonstrate the fulfillment of the evaluated trajectory with the on-board control system of the vehicle in provision for UAS field testing. Finally, the planning strategy is applied to two case studies so as to present the feasibility of a more efficient autonomous UAS path planning.