Research On UAV Path Planning Based On Neural Networks

Unmanned aerial vehicle(UAV)has been widely applied in military and civil application,because of its less space needed for take-off and landing,the operating performance in high intensive environment,the obstacles and the strong ability of flight attitude to keep advantage,very suitable for near-earth observation,forest fire prevention,aerial photography,traffic patrol inspection tasks and so on.Unmanned aerial vehicle is difficult to control because of multivariate,the under actuated,nonlinear,poor stability and more complex features.Therefore,the control problem of UAV has been got wide attention by research community,and become a research hotspot in control area.Based on neural network path optimization and wave propagation algorithm,the path optimization problem has been researched,and verified the validity of the algorithm through the Matlab.Firstly,digital map has been investigated for uav ground station operator,which provided information on the terrain data and the location of unmanned aerial vehicle,then focus on the terrain application for unmanned aerial vehicle.Secondly,the path optimization algorithm has been investigated,through wave propagation to set up neural networks path optimization algorithm to realize the shortest path optimization for unmanned aerial vehicle.Thirdly,the threating task path optimization algorithm has been investigated,through wave propagation to set up neural networks path optimization algorithm to realize the shortest path optimization for threatening unmanned aerial vehicle.Finally,the feasibility and effectiveness of the verification algorithm has been realized the unmanned aerial vehicle route optimization problem through Matlab and realized the path planning for unmanned aerial vehicle.