Unmanned aerial vehicle multi-task path planning method and system based on ant colony algorithm

The invention discloses an unmanned aerial vehicle multi-task path planning method and system based on an ant colony algorithm. The method comprises the following steps: determining a multi-task constraint condition of the unmanned aerial vehicle; the constraint conditions comprise a minimum turning radius constraint, a minimum track segment length constraint and a maximum voyage constraint; rasterizing the multi-task flight environment of the unmanned aerial vehicle to obtain a rasterized flight environment; under the constraint condition and in the rasterized flight environment, iteratively calculating an optimal path by adopting an ant colony algorithm; in the iterative calculation process, updating pheromone concentration according to a pheromone updating rule to perform path search, and selecting a search path with the minimum total path cost as an optimal path; the total path cost comprises path length cost, flight height cost and path turning frequency cost. According to the method, the total path cost