Efficient Trajectory Planning for WSN Data Collection with Multiple UAVs

This chapter discusses the problem of trajectory planning for WSN (Wireless Sensor Network) data retrieving deployed in remote areas with a cooperative system of UAVs (Unmanned Aerial Vehicles). Three different path planners are presented in order to autonomously guide the UAVs during the mission. The missions are given by a set of waypoints which define WSN collection zones and each UAV should pass through them to collect the data while avoiding passing over forbidden areas and collisions between UAVs. The proposed UAV trajectory planners are based on Genetics Algorithm (GA), RRT (Rapidly-exploring Random Trees) and RRT* (Optimal Rapidly-exploring Random Trees). Simulations and experiments have been carried out in the airfield of Utrera (Seville, Spain). These results are compared in order to measure the performance of the proposed planners.