Autonomous aerial refueling is a key enabling technology for both manned and unmanned aircraft where extended flight duration or range are required. The results presented within this paper offer one potential vision-based sensing solution, together with a unique test environment. A hierarchical visual tracking algorithm based on direct methods is proposed and developed for the purposes of tracking a drogue during the capture stage of autonomous aerial refueling, and of estimating its 3D position. Intended to be applied in real time to a video stream from a single monocular camera mounted on the receiver aircraft, the algorithm is shown to be highly robust, and capable of tracking large, rapid drogue motions within the frame of reference. The proposed strategy has been tested using a complex robotic testbed and with actual flight hardware consisting of a full size probe and drogue. Results show that the vision tracking algorithm can detect and track the drogue at real-time frame rates of more than thirty frames per second, obtaining a robust position estimation even with strong motions and multiple occlusions of the drogue

This paper addresses the problem of collision avoidance with moving obstacles for unmanned aerial vehicles. It is assumed that obstacle detection and tracking can be achieved 60 seconds prior to collision. Such a time horizon allows on-board trajectory re-planning with updated constraints due to intruder and ownship dynamics. This trajectory generation problem is solved using a direct method, meaning the problem is transcripted to a nonlinear programming problem and solved with an optimization method. The main challenge in trajectory generation framework is to reliably provide a feasible (safe and flyable) trajectory within a deterministic time. In order to improve the method's reliability, a Monte Carlo analysis is used to investigate the convergence properties of the optimization process, the properties of the generated trajectories and their effectiveness in obstacle avoidance. The results show that the method is able to converge to a feasible and near-optimal trajectories within two seconds, except in very restrictive cases. Moreover, the dynamic feasibility of the generated trajectories is verified with nonlinear simulations, where the trajectory generation is integrated with the six degree-of-freedom nonlinear model of a fixed-wing research vehicle developed at Cranfield University. The results show that the generated trajectories can be tracked with a proposed two-degree-of-freedom control scheme. The improved convergence, fast computation and assured dynamic feasibility pave the way for on-board implementation and flight testing.

This paper provides a comparative performance analysis of a hands-on-throttle-and-stick (HOTAS) cursor control device (CCD) with other suitable CCDs for an aircraft cockpit: an isotonic thumbstick, a trackpad, a trackball, and touchscreen input. The performance and characteristics of these five CCDs were investigated in terms of throughput, movement accuracy, and error rate using the ISO 9241-9 standard task. Results show statistically significant differences ( p < 0.001) between three groupings of the devices, with the HOTAS having the lowest throughput (0.7 bits/s) and the touchscreen the highest (3.7 bits/s). Errors for all devices were shown to increase with decreasing target size ( p < 0.001) and, to a lesser effect, increasing target distance ( p < 0.01). The trackpad was found to be the most accurate of the five devices, being significantly better than the HOTAS fingerstick and touchscreen ( p < 0.05) with the touchscreen performing poorly on selecting smaller targets ( p < 0.05). These results would be useful to cockpit human-machine interface designers and provides evidence of the need to move away from, or significantly augment the capabilities of, this type of HOTAS CCD in order to improve pilot task throughput in increasingly data-rich cockpits.

Unmanned aerial systems are increasingly prevalent in the defense and civil sectors, and there is a desire to increase their effectiveness and versatility by adding the capability to perform air-to-air refueling. Furthermore, the burden on pilots can be significantly reduced by implementing automated flight control in refueling operations. Existing work on automated air-to-air refueling focuses on leader/follower architectures, which do not fully exploit all available control authority. This paper presents a collaborative control design that may be used to coordinate the flying boom and receiver aircraft. The control scheme is implemented in a refueling scenario modeled with a detailed air-to-air refueling simulation model. Results suggest that employing a weighted collaborative target point between the flying boom and receiver improves the docking time and reduces the susceptibility to disturbances because the errors for the tracking controllers are weighted by the displacement between the two objects. However, to maintain the docking in the operational envelope, a virtual structure is required to suitably anchor the target point.

This paper presents a range control approach for implementing hard geofencing for unmanned air vehicles (UAVs), and especially remotely piloted versions (RPVs), via a proposed anticipatory range calculator. The approach employs turning circle intersection tests that anticipate the fence perimeter on approach. This ensures the vehicle turns before penetrating the geofence and remains inside the allowable operational airspace by accounting for the vehicles’ turning dynamics. Allowance is made for general geozone shapes and locations, including those located at the problematic poles and meridians where nonlinear angle mapping is dealt with, concave geozones, narrow corners with acute internal angles, and transient turn dynamics. The algorithm is shown to prevent any excursions using a high-fidelity simulation of a small remotely piloted vehicle. The algorithm relies on a single tuning parameter which can be determined from the closed-loop rise time in the aircraft’s roll command tracking.