Cooperative Control of Small UAVs for Naval Applications Isaac I. Kaminer*, Oleg A. Yakimenko*, Vladimir N. Dobrokhodov*, Mariano I. Lizarraga*, and Antonio M. Pascoal** * Department of Mechanical and Astronautical Engineering, Naval Postgraduate School, Monterey CA ** Department of Electrical Engineering, Instituto Superior Técnico, Lisbon Portugal Abstract - This paper addresses the development of a coopera- tive control algorithm used to launch and recover a fleet of small UAVs from a ship. The key features of the algorithm include trajectory generation for multiple UAVs that accounts for their aerodynamic characteristics and guarantees decon- fliction, particularly on final approach, and path following control for multiple UAVs to track these trajectories. The proposed control approach is sufficiently flexible to allow for multiple formation configurations and sequential landing pat- terns. The paper includes simulation results and ends with conclusions and recommendations for future work. I. INTRODUCTION HIS paper addresses the development of a shipboard autoland system for multiple small unmanned air vehi- cles (UAVs). The typical mission scenario includes a ship under way that has launched and now needs to recover a team of small UAVs. (Specific UAVs considered are Silver Foxes (SFs) produced by ACR of Tucson, AZ.) It is as- sumed that initially the UAVs are flying in formation to- wards the ship. The approach for sequential autoland of the UAV formation presented in this paper includes: i) real-time trajectory generation for each UAV so as to bring it to the top of the glideslope from its place in the formation during a specified time slot (Segment 1 on Fig.1). These trajectories must guarantee deconfliction; furthermore, the time slots are selected to provide the UAV team aboard the ship sufficient time to retrieve each UAV from the net; ii) real-time glideslope generation to bring each UAV from the top of glideslope to the center of the net, mov- ing with the ship (of course this Segment 2 is actually being computed first to provide the final point for the Segment 1); iii) a control strategy to force each UAV to track the tra- jectories developed in steps 1 and 2. This paper is organized as follows. Section 2 discusses the implementation of the direct method of optimal control developed in [1] and modified here to guarantee sequential collision-free arrival of multiple UAVs in step 1. Section 3 addresses the construction of a stabilized glideslope that brings each UAV to the center of the net. Sections 4 ad- dresses control system design and simulation results. Sec- tion 5 discusses the hardware implementation and presents hardware-in-the-loop simulation results. The paper ends with the conclusions and a description of future work. Segment 2: Stabilized glideslope tracking Segment 2: Stabilized glideslope tracking Segment 1: Glideslope capture (from any initial condition) Segment 1: Glideslope capture (from any initial condition) Autoland initiation point Glideslope capture Engine shut down ~25m before net Two DGPS receivers at net’s corners and barometer Fig. 1. Small UAV shipboard autoland strategy. II. NEAR-OPTIMAL REAL-TIME TRAJECTORIES GENERATION This section presents the theory and algorithms for real- time trajectory generation. This theory is first presented for the case of a single UAV as in [1], after which it is shown how the trajectory optimization problem can be reformu- lated for a group of UAVs flying in formation to provide sequential collision-free landing (glideslope capturing). T