| With the rapid development of automation technology and the rapid improvement of aviation level,UAV has been widely used in military,civil and other fields as an important research and application tool.UAV flight path planning refers to generating a flightable path between the starting point and the target point and selecting the optimal path for flight.The optimization technology of UAV flight path has always been one of the key and difficult points in the field of UAV research.Flight path planning is of great significance for improving the success rate and survival probability of UAV missions.Therefore,this thesis aims to improve the accuracy and performance of UAV flight path planning,so as to further improve the auxiliary decision-making role of ground station for pilot operation,so as to better help UAV to complete the task.This thesis takes online and offline flight path planning as the main research direction,and studies the auxiliary decision-making problem of UAV flight path.Firstly,this thesis makes an in-depth analysis of offline flight path planning and online flight path planning,and proposes a scientific and reasonable path model to solve the optimal decision problem of actual UAV flight path.In this thesis,the UAV flight environment is transformed into a mathematical model that can be solved by algorithm,which lays a foundation for subsequent research.Aiming at the off-line flight path planning of fixed obstacles,this thesis proposes an off-line flight path planning model of UAV based on POA(Preaching Optimization Algorithm)algorithm.The model takes into account the actual motion constraints,introduces a rotating coordinate system,and can efficiently generate the optimal or suboptimal path from the starting point to the target point.Through a large number of simulation experiments and data analysis,the planning success rate of the algorithm in this thesis is significantly better than that of other algorithms such as CIPSO under 100 different terrain conditions,avoiding the situation of falling into local optimal solution.In addition,this thesis also introduces the method of environmental model optimization to further improve the accuracy and performance of offline flight path planning.For online flight path planning,this thesis proposes an online flight path planning method for UAV based on rolling window in dynamic obstacle environment.This method can intelligently select a personalized collision avoidance strategy according to different obstacle conditions,and further improve the quality of the planning results by introducing the original track attraction factor,and try not to deviate from the original track while re-planning the flight path.Through a large number of tests and verifications,this thesis verifies the good performance and feasibility of the method in various dynamic obstacle environments. |
