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ROTARY-WING UAVS TRAJECTORY PLANNING BY DISTRIBUTED LINEAR MPC WITH RECONFIGURABLE COMMUNICATION NETWORK TOPOLOGIES

Abstract In this paper, a distributed approach to Model Predictive Control (MPC)-based trajectory planning for rotary-wing UAV (Unmanned Aerial Vehicle) communication network topologies under radio path loss constraints is proposed. The goal is to find trajectories that are safe with respect to grounding and collision, fuel efficient and satisfy criteria for communication such that the UAVs form chains to multiple targets with given radio communication capacities. The MPC-based optimization sub-problems are computed autonomously within each UAV, using convex quadratic programming, with the requirement that each UAV communicates its current measured position to all other UAVs. In addition, a simple coordination between UAVs allows for the communication network topology to be reconfigured in case of failures or radio path loss changes. The control performance of the distributed linear MPC trajectory planning is studied based on a simulation case with four UAVs and two targets.