Research on Logistics Drone Trajectory Planning Based on Improved Ant Colony Algorithm
Research is conducted on the problem of unmanned aerial vehicle(UAV)trajectory planning in logistics distribution,taking into account factors such as UAV performance,and airspace environment.With the goal of minimizing total economic cost,minimizing time,and maximizing safety,a logistics UAV trajectory planning model is established under multiple constraint conditions.Firstly,improve the pheromone distribution of the traditional ant colony algorithm,improve the search accuracy of the heuristic function,and then overlay the beetle whisker algorithm for quadratic programming.Use the improved algorithm to solve the above model.The research results show that the algorithm proposed in this paper can effectively reduce the running time of the algorithm,and in terms of the planned optimal trajectory,the improved algorithm has the shortest and better optimal trajectory length.It ensures the fastest arrival at the target point while also ensuring the safe avoidance of obstacle threats during drone flight,proving the effectiveness of the improved algorithm.
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维普
