Time Optimal Multi-UAV Path Planning for Gathering its Data from Roadside Units

In this paper, we address the problem of path planning for multiple unmanned aerial vehicles (UAVs), to gather data from a number of roadside units (RSUs). The problem involves finding time-optimal paths for multiple UAVs so that they collectively visit all the RSUs, while also exchanging information at their own point when they fly from a starting point to the final location. We solve the problem by applying modified evolutionary methods based on genetic algorithm (GA) and harmony search (HS). The modified search methods seek to determine the overall shortest path utilizing various evolutionary operators regarding each UAV which has identical properties at the start location. Numerical results are introduced under different scenarios and the performances of the proposed algorithms are evaluated.