Optimal path planning for an unmanned aerial vehicle

This paper presents an extended approach of local optimization strategy (ELOS) for generation of a collision free shortest distance path for the unmanned aerial vehicle (UAV). Autonomous vehicles are being used to perform missions in hazardous environments. The real task lies in generating an optimal path in these adversarial environments. Since the UAV operates in a dynamic environment, the ELOS aims at an optimal collision free path, with emphasis on the varying positions of the obstacle. The ELOS generates the path, depending on two factors: onboard sensory measurements of the position of the obstacle at each instant of time and the distance to destination. Simulation results show that ELOS can be effectively used as an optimal path generation strategy for UAVs functioning in dynamic environments.