Cooperative optimization of task allocation and trajectory planning for multimission in heterogeneous UAV cluster

This article proposes a cooperative optimization algorithm of task allocation and trajectory planning for multi-mission in heterogeneous unmanned aerial vehicle (UAV) cluster. The basis of the proffered algorithm is to establish constraint and threat models to simultaneously minimize range, maximize value gain and survival probability under the constraints of task payload, range and task requirement. With this, derive the objective function for heterogeneous UAV cluster within multi-mission, and adopt it as a metric for assessing the performance of the cooperative optimization in task allocation and trajectory planning. It is revealed that the formulated cooperative optimization problem is a multi-objective, nonlinear and non-convex optimization model due to its multiple decision variables and constraints. By introducing the roulette wheel selection (RWS) principle and the elite strategy (ES), an ant colony optimization (ACO) with ES the capability to solve the complex optimization model. The simulation results indicate that the proposed algorithm is superior and more efficient compared to other approaches.