Research On The Fast 3D Route Path Planning Algorithm For Uav

In recent years, UAV is developing rapidly in domestic,which is characterized by low cost,strong survival ability,convenient application and no casualties,UAVs are widely used in civilian areas, flight path planning algorithm plays a role play a decisive role in order to achieve the autonomous flight. This paper mainly studied the path planning algorithm for UAV flight,the aims are to improve the survival ability and mission capability.In the aspect of spatial terrain modeling,this paper chose a method based on the initial data interpolation to construct 3D terrain,using this method can effectively carry out data update,better meet the real-time demand, and in the practical application, and has more practical application value. In addition, the current route planning algorithm of mature respectively describes the classification, advantages and disadvantages and the planning algorithm of mature respectively describes the classification, advantages of the analysis of these algorithms, selected after the algorithm to do the preparatory work.In path constraint aspect, threat environment and self constraint are considered in this paper,the corresponding mathematical model of UAV flight must consider the flying height and pitch angle, a maximum range of constraints is established, then the paper introduces the high frequency UAV threats in the flight environment a mathematical model is given,and threat index formula and the corresponding.Path planning is mainly divided into two aspects,which are static planning and dynamic planning,static planning in this paper chose the sparse A* planning algorithm with global optimum characteristics, which is also known as the SAS algorithm.The constraints are integrated into the path planning in order to reduce the useless nodes.In the dynamic route planning,this paper adopted the method of hierarchical strategy planning.Firstly,quote the heuristic function into the improved artificial potential field algorithm for pre-planning,secondly,calculate the curvature of every peak point,and then chose the peak value of curvature as the guide point. Finally, call SAS algorithm planning between adjacent guide points. This method can avoid the randomness of the tracks, and can be close to the optimal route in the track distance, and can save the time of the algorithm route search.In this paper, various algorithms are simulated, which improved the Correctness and feasibility of the hierarchical strategy.