UAVs Formation Flight under Multiple Obstacle and Communication Constraints

TL;DR

This paper presents a novel multi-objective optimization approach for UAV formation reconfiguration in complex environments, enhancing communication and reducing energy consumption through advanced mathematical modeling and algorithms.

Contribution

It introduces a new optimization framework transforming multi-objective problems into single convex problems using Pareto theory and primal-dual algorithms for UAV formation reconfiguration.

Findings

Lowest energy consumption achieved in simulations

Maintains UAV formation connectivity under constraints

Efficient reconfiguration in complex environments

Abstract

In order to improve the communication of the UAV network when the UAV formation in a complex military mission environment. This paper proposed formation reconfiguration strategy under complexities mission environment. We take the problem of multi-UAV formation reconfiguration transform into nonlinear inequality constraints optimization by mathematic approach. (i)design multi-objective multi-constraints optimization function for different task of UAVs and complexities mission environment, and get an optimal model.(ii) Using Pareto optimal theory transform the multi-objective optimization problem into single optimization problem.(iii)finally, we apply the primal-dual Newton interior point algorithm to process the convex optimal problem. In order to verify the high efficiency of this method, a series of simulation experiments are designed. The experiment shows that the method in this paper has the lowest energy consumption while maintaining the connectivity of the UAV formation network.