| Summary: | 碩士 === 國立虎尾科技大學 === 自動化工程系碩士班 === 107 === To improve the path planning algorithm for UAV swarm by adding the mathematical model of time dimension to achieve a 4D mission assignment that including a path programming to arrive target locations at a specified time, is the object of this research.
To solve this 4D dynamic path programming problem for UAV swarm mission, we use the 2-phase Tabu search with 2-Opt exchange method and A* search as the 3D path programming algorithm. First, let distance as a cost function for path programming, on the premise that load balance distance, and minimum total distance for the optimization of algorithm. Second, acquire an equation from MATLAB which is according to the flight database collected in this research, fitting the 5 parameters that affect the mission time to get the sextic equation. Finally, substitute the path planning result and set time into the equation, find the approximate velocity of the variable by Newton's method, in order to change the flight velocity of the path to control the completion time, and feasibility analysis of this mission. Expect quadcopter UAV swarm can not only load balanced but also reach the most efficient to complete the specified mission at the specified time, through the ground control system developed by this research, sequencing or simultaneous arrival of UAV swarm mission can be achieve.
The final experiments successfully showed each UAV in the swarm can arrive assigned target points at specific times. The average error in this mission time control experiment was less than 3.6%.
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