GPGPU accelerated potential field based autonomous air refueling approach for UAVs

In this study autonomous air refueling approach will be discussed and the aim of the paper to extend the endurance of an Unmanned Aerial Vehicle by performing air refueling task with minimal human support. One of the major components of the air refueling is autonomous navigation and path planning algorithms. Potential field based autonomous air refueling path planning approach will be designed in this study and the simulation results will be introduced. Another factor for the air refueling is rapid change manner dynamic environment conditions. This factor brings computational complexities of the potential fields. To solve computational bottlenecks, the parallel computation techniques are applicable in real time applications. Today one of the major parallel computing platforms are Graphic Processor Units with the General Purpose Programming support. By using GPGPU capabilities, accelerated potential field based autonomous air refueling approach for the Unmanned Aerial Vehicles is designed and simulation results successfully shared with this study.