Route Optimization of Unmanned Aerial Vehicle by using Reinforcement Learning

Abstract

Abstract The study proposes the machine learning based algorithm for autonomous vehicle. The dynamic characteristic of unmanned aerial vehicle and real time disturbances such as wind current, obstacles are considered. The novelty of the work lies in the introduction of reinforcement learning for achieving optimized path which can be followed by the unmanned aerial vehicles to complete the tour from initial to destination point. The feasible optimal route may be found by incorporating the L algorithm with a reasonable optimality and computational cost when map and current field data are given.