Abstract

This paper investigates cooperative trajectory planning of multiple unmanned combat aerial vehicles (multi-UCAV) in performing autonomous cooperative air-to-ground target attack missions. By integrating an approximate allowable attack region model, several constraint models, and a multicriterion objective function, the problem is formulated as a cooperative trajectory optimal control problem (CTOCP). Then, a virtual motion camouflage (VMC) for cooperative trajectory planning of multi-UCAV, combining with the differential flatness theory, Gauss pseudospectral method (GPM), and nonlinear programming, is designed to solve the CTOCP. In particular, the notion of the virtual time is introduced to the VMC problem formulation to handle the temporal cooperative constraints. The simulation experiments validate that the CTOCP can be effectively solved by the cooperative trajectory planning algorithm based on VMC which integrates the spatial and temporal constraints on the trajectory level, and the comparative experiments illustrate that VMC based algorithm is more efficient than GPM based direct collocation method in tackling the CTOCP.

Highlights

  • Nowadays, it is an active research area to perform autonomous cooperative air-to-ground target attack (CA/GTA) missions using multiple unmanned combat aerial vehicles [1]

  • This paper investigates cooperative trajectory planning of multiple unmanned combat aerial vehicles in performing autonomous cooperative air-to-ground target attack missions

  • To obtain optimal or suboptimal cooperative trajectories, the cooperative trajectory planning for the CA/GTA missions can be formulated as a cooperative trajectory optimal control problem (CTOCP)

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Summary

Introduction

It is an active research area to perform autonomous cooperative air-to-ground target attack (CA/GTA) missions using multiple unmanned combat aerial vehicles (multi-UCAV) [1]. Some numerical simulations [22,23,24] suggest that its computational speed could be much faster than the pseudospectral methods Motivated by these advantages, this paper employs virtual motion camouflage approach to develop cooperative trajectory planning algorithms. Reference [28] proposed a divide and conquer hierarchical approach in three levels to solve the UAV formation flight trajectory plan problem considering dynamics, state, and control variable inequality and equality constraints. These approaches mentioned above could generate collision-free trajectories, but the temporal cooperation was ignored.

Modeling
Problem Formulation
Virtual Motion Camouflage Based Cooperative Trajectory Planning
Virtual Motion Camouflage and Problem Formulation in the Output Space
Numerical Examples
Initial guess
Example 1
Example 2
Conclusions
Objective function value
Full Text
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