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In this paper, the authors propose a cooperative formation control strategy with collision-avoidance capability for a multi-unmanned aerial vehicle (UAV) system using decentralized model predictive control (MPC) and consensus-based control. Consensus-based control algorithms are applied for formation flying in three-dimensional space. However, UAVs where these formation control algorithms are applied have not the ability to avoid collisions. Decentralized model predictive control (MPC) is applied to generate control inputs for formation flying with collision-avoidance capability. Using decentralized MPC, each UAV plans only its own action to track the trajectory specified by the formation control algorithm within the feasible regions satisfying collision-avoidance. The authors show how the optimization problems with coupled constraints such as collision-avoidance can be solved by each decoupled UAV in parallel with the other UAVs so that the decisions independently taken by each UAV can ensure consistency in coupled constraints of collision-avoidance. The computation time is also taken into account because it is a crucial factor to apply MPC to actual UAVs. Finally, the proposed approach is validated by some simulations.
Kuriki et al. (Wed,) studied this question.