Three-Dimensional Path Planning And Visualization For UAV Under Real Terrain

In recent years,with the progress in autonomous control,signal processing,and communication technologies,UAV’s autonomous flight technology has made considerable development and tremendous progress.Utilizing its own advantages,UAV can partially or completely replace humankind to complete certain tasks with high risk factors,so they have been widely used in military and civilian fields.Before the UAV performs its mission,it has to plan the flight path needed for the successful completion of the mission according to the flight environment and mission requirements,that is,the UAV flight path planning,which is an important part of the UAV mission planning system.It is also a technical guarantee for the UAV to achieve safe and reliable autonomous flight,which can greatly improve the combat effectiveness of UAV.This thesis first introduced the research background of the UAV flight path planning technology,carried out the formal description of the path planning,elaborated on the commonly used space planning methods,the main constraints of the path planning and the comprehensive performance costs,especially the planning algorithm,which is the core of the three-dimensional path planning of UAV.As a result,it has been found that the existing path planning methods are mainly based on simulation scenarios,while the methods based on the 3D visualization platform are rarely studied.To solve this problem,based on the 3D visualization platform,the real terrain data is used to model the UAV flight in the 3D planning space.Several constraints are considered,including the constraints on the maneuverability of the UAV and obstacles or threat constrains in the flight environment.The coordinate system transformation of the three-dimensional planning space was studied,extracted the position information of the waypoint of the UAV by spatial interpolation method,and carried out relevant modeling experiments.On this basis,the ant colony algorithm is used to plan the mission path of the UAV,and the original ant colony algorithm is improved,which mainly includes the design of the heuristic function and the pheromone update mechanism,and elaborates the flow of the algorithm.The ant colony algorithm parameter combination experiment was carried out.The optimal parameter combination was used to plan the flight path for UAV from the starting point to the target point to meet the various performance constraints and optimal cost requirements,then a simulated UAV flight verification was performed.Furthermore,in order to deal with the unknown and unpredictable threats in the UAV flight process,a solution for path re-planning is proposed.After detailed description of this method,simulations are performed through experiments.The results show that the re-planned path can effectively avoid unexpected and unknown threats.Finally,based on Microsoft Visual Studio 2010,the 3D visual path planning software of UAV was designed to realize the functions of parameter adjustment,path storage and read,and flight simulation.The display of the planning results was intuitive and had enhanced the decision of UAV.