UAV Mission Planning Based on Fish Swarm-ant Colony Optimization
Wenbiao He, Wenguang Li, Yongjiang Hu · 2023
Addressing the problem of how multiple drones can quickly reconnoiter target points in a complex environment. A task planning algorithm to improve the fish-colony hybrid algorithm is proposed. First of all, according to the reconnaissance requirements of different importance targets in complex environments, a mission planning model with the greatest reconnaissance benefit as the objective function is established. Second, the data is pre-searched by a simplified artificial fish swarm algorithm, the initial pheromone distribution is generated, and the pheromone is passed into the improved ant colony algorithm to solve the model. Experimental simulation proves that the algorithm can solve the problem of task allocation and path planning in an integrated manner, and the convergence speed and global optimization ability of the traditional ant colony algorithm are improved.