A Path Planning Optimization Algorithm Based on Particle Swarm Optimization for UAVs for Bird Monitoring and Repelling – Simulation Results
Ricardo Mesquita, Pedro Dinis Gaspar · 2020 International Conference on Decision Aid Sciences and Application (DASA) · 2020
Bird damage to orchards causes large monetary losses to farmers. The application of traditional methods such as bird cannons and tree netting became inefficient in the long run, along with its high maintenance and reduced mobility. Due to their versatility, Unmanned Aerial Vehicles (UAVs) can be very useful to solve this problem. However, due to their low autonomy it is necessary to evolve flight planning. In this article, an optimization algorithm for path planning of UAVs based on Particle Swarm Optimization (PSO) is presented. This technique was used due to the need of an entry optimization algorithm to start the initial tests. The PSO algorithm is a simple and has few control parameters while maintaining a good performance. This path planning optimization algorithm aims to manage the drone's distance and flight time, applying optimization and randomness techniques, to be able to overcome the disadvantages of other systems. The performance of the proposed algorithm was tested in a tree case simulation that represents all the possible cases.