Autonomous docking for airborne energy transfer is an important unmanned aerial vehicle capability that has yet to be accomplished. The implications of this technology are far reaching because vehicle endurance can be significantly extended without requiring additional onboard energy storage or environmental energy collection. A major barrier to docking with a drogue is reliable and accurate knowledge of the drogue's state, relative to the aircraft that is performing the manoeuvre. We address this by propagating a derived cable-drogue dynamic model using onboard sensor measurements, then correcting the state and aerodynamic coefficients with air-to-air visual observations. The approach is verified through a series of close formation flights with a marker based infra-red vision system. These flights represent significant progress toward an autonomous docking demonstration.

Unmanned aerial vehicle (UAV) formation flight can vastly increase operational range and persistence through autonomous aerial refuelling or efficient flight on a wingman's wake vortices. Differencing individual UAV state estimates is not sufficiently accurate for close formation operations and must be augmented with vehicle-to-vehicle observations. To this end, we propose a quaternion based unscented Kalman filter to fuse information from each UAV sensor suite with relative vision observations. The result is a vastly improved relative state estimate that is resilient to brief vision dropouts and degrades gracefully during extended dropouts. Simulated formation flight results validate the approach and provide a numerical analysis of the algorithm performance. Ground based experiments demonstrate the algorithm running in real-time on a dual-UAV system. This represents a significant step towards an airborne implementation.

Fixed-wing Unmanned Aerial Vehicle (UAV) rendezvous is necessary for reduced fuel consumption during leader-follower formation flight. We propose a heuristic direct search algorithm that plans a time-optimal path for a follower UAV to rendezvous with a leader whose future path is known and unchanging. The kinematic constraints of the UAV are considered and discontinuities inherent to the minimum-length paths are dealt with. Experiments using quadrotors to emulate fixed-wings, demonstrate the algorithm planning and replanning optimal paths to rendezvous in real-time.