Research On Multi-Objective Path Planning Algorithm For High-Altitude Long-Endurance Unmanned Aerial Vehicle

Modern unmanned aerial vehicles(UAV)applications are not limited to performing reconnaissance missions,but can also be used as combat weapons to directly confront the enemy.Among the many subsystems of the UAV control module,the research work of the path planning system is becoming more and more important.The core of the path planning is to study the path planning algorithm.The path planning algorithm is not only to complete the task,but also meets Under the restriction of UAV flight characteristics,a trajectory that avoids all threats and has a better path distance is planned according to multi-target constraints.The flight characteristics of high-altitude long-endurance(HALE)UAVs and low-altitude UAVs are different.Low-altitude UAVs are mainly used to perform short-range missions,and the flight range is small.Most flight path planning algorithms uses two points' distance the straight line distance is calculated.However,the HALE UAVs mainly performs long-range reconnaissance and strike tasks,and the track coverage is wide.The use of a flat straight-line distance from the calculation of the distance will cause a large error.This paper considers the influence of the curvature of the earth on the calculation of the track distance,and the HALE UAV basically adopts the fixed altitude flight assumption.The study of the HALE UAV flight path planning problem includes the following aspects:(1)A Surface path planning method based on dimension reduction mapping is proposed.First of all,the Gauss projection is used to calculate the starting point,target point and threat information represented by the three-dimensional geodetic coordinates to the Gauss two-dimensional plane coordinate system,and then the optimal trajectory obtained after planning is calculated using the Gauss projection and displayed to three-dimensional geodetic coordinates system.(2)A global static planning method of long-range surface path is proposed.Under the multi-objective cost constraint that comprehensively considers the known threat and fuel cost,the multi-objective fuzzy optimization method is used to eliminate the magnitude difference of each cost.Based on the well-recognized Dijkstra,the best algorithm for solving the shortest path to two points,in order to eliminate Dijkstra's easy to fall into the local minimum and unnecessary track turns to make the obtained track distance too long,the Dijkstra algorithm and the simulated annealing algorithm is combined to generate a new Algorithm of Dijkstra-SA.(3)The online dynamic planning method of long-distance surface path is studied.Based on the researched new combined algorithm Dijkstra-SA,the HALE UAVs is respectively subjected to local online path planning and global online path planning.In this paper,the proposed HALE UAVs path planning method is simulated and verified.By comparing the planning results of Multiple algorithm and Dijkstra-SA algorithm,the new algorithm Dijkstra-SA has better planned ability.By comparing the results of local and global online path planning,the practicability and effectiveness of Dijkstra-SA algorithm is verified,and the algorithm The dimension reduction mapping strategy is adopted,which can be applied to the path planning of large latitude and longitude aircraft such as HALE UAVs.