Situation awareness for UAV operating in terminal areas using bearing-only observations and circuit flight rules

Situation awareness is required for an Unmanned Aerial Vehicle (UAV) when it makes an arrival at an uncontrolled airfield. Since no air traffic control service is available, the UAV needs to detect and track other traffic aircraft by using its onboard sensors. General aviation pilots obtain enough situation awareness to operate in these environments, only using their vision and radio messages heard from other traffic aircraft. To improve the target tracking performance of a UAV, the circuit flight rules and standard radio messages are incorporated to provide extra knowledge about the target behaviour. This is achieved by using the multiple models to describe the target motions in different flight phases and characterising the phase transition in a stochastic manner. Consequently, an interacting multiple model particle filter with state-dependent transition probabilities is developed to perform Bayesian filtering with bearing-only observations from a vision sensor

Autonomous terminal area operations for unmanned aerial systems

After many years of successful operation in military domains, Unmanned Aerial Systems (UASs) are generating significant interest amongst civilian operators in sectors such as law enforcement, search and rescue, aerial photography and mapping. To maximise the benefits brought by UASs to sectors such as these, a high level of autonomy is desirable to reduce the need for highly skilled operators. Highly autonomous UASs require a high level of situation awareness in order to make appropriate decisions. This is of particular importance to civilian UASs where transparency and equivalence of operation to current manned aircraft is a requirement, particularly in the terminal area immediately surrounding an airfield. This thesis presents an artificial situation awareness system for an autonomous UAS capable of comprehending both the current continuous and discrete states of traffic vehicles. This estimate forms the basis of the projection element of situation awareness, predicting the future states of traffic. Projection is subject to a large degree of uncertainty in both continuous state variables and in the execution of intent information by the pilot. Both of these sources of uncertainty are captured to fully quantify the future positions of traffic. Based upon the projection of future traffic positions a self separation system is designed which allows an UAS to quantify its separation to traffic vehicles up to some future time and manoeuvre appropriately to minimise the potential for conflict. A high fidelity simulation environment has been developed to test the performance of the artificial situation awareness and self separation system. The system has demonstrated good performance under all situations, with an equivalent level of safety to that of a human pilot

Autonomous Close Formation Flight of Small UAVs Using Vision-Based Localization

As Unmanned Aerial Vehicles (UAVs) are integrated into the national airspace to comply with the 2012 Federal Aviation Administration Reauthorization Act, new civilian uses for robotic aircraft will come about in addition to the more obvious military applications. One particular area of interest for UAV development is the autonomous cooperative control of multiple UAVs. In this thesis, a decentralized leader-follower control strategy is designed, implemented, and tested from the follower’s perspective using vision-based localization. The tasks of localization and control were carried out with separate processing hardware dedicated to each task. First, software was written to estimate the relative state of a lead UAV in real-time from video captured by a camera on-board the following UAV. The software, written using OpenCV computer vision libraries and executed on an embedded single-board computer, uses the Efficient Perspective-n-Point algorithm to compute the 3-D pose from a set of 2-D image points. High-intensity, red, light emitting diodes (LEDs) were affixed to specific locations on the lead aircraft’s airframe to simplify the task if extracting the 2-D image points from video. Next, the following vehicle was controlled by modifying a commercially available, open source, waypoint-guided autopilot to navigate using the relative state vector provided by the vision software. A custom Hardware-In-Loop (HIL) simulation station was set up and used to derive the required localization update rate for various flight patterns and levels of atmospheric turbulence. HIL simulation showed that it should be possible to maintain formation, with a vehicle separation of 50 ± 6 feet and localization estimates updated at 10 Hz, for a range of flight conditions. Finally, the system was implemented into low-cost remote controlled aircraft and flight tested to demonstrate formation convergence to 65.5 ± 15 feet of separation

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Using learning from demonstration to enable automated flight control comparable with experienced human pilots

Modern autopilots fall under the domain of Control Theory which utilizes Proportional Integral Derivative (PID) controllers that can provide relatively simple autonomous control of an aircraft such as maintaining a certain trajectory. However, PID controllers cannot cope with uncertainties due to their non-adaptive nature. In addition, modern autopilots of airliners contributed to several air catastrophes due to their robustness issues. Therefore, the aviation industry is seeking solutions that would enhance safety. A potential solution to achieve this is to develop intelligent autopilots that can learn how to pilot aircraft in a manner comparable with experienced human pilots. This work proposes the Intelligent Autopilot System (IAS) which provides a comprehensive level of autonomy and intelligent control to the aviation industry. The IAS learns piloting skills by observing experienced teachers while they provide demonstrations in simulation. A robust Learning from Demonstration approach is proposed which uses human pilots to demonstrate the task to be learned in a flight simulator while training datasets are captured. The datasets are then used by Artificial Neural Networks (ANNs) to generate control models automatically. The control models imitate the skills of the experienced pilots when performing the different piloting tasks while handling flight uncertainties such as severe weather conditions and emergency situations. Experiments show that the IAS performs learned skills and tasks with high accuracy even after being presented with limited examples which are suitable for the proposed approach that relies on many single-hidden-layer ANNs instead of one or few large deep ANNs which produce a black-box that cannot be explained to the aviation regulators. The results demonstrate that the IAS is capable of imitating low-level sub-cognitive skills such as rapid and continuous stabilization attempts in stormy weather conditions, and high-level strategic skills such as the sequence of sub-tasks necessary to takeoff, land, and handle emergencies

An investigation into hazard-centric analysis of complex autonomous systems

This thesis proposes a hypothesis that a conventional, and essentially manual, HAZOP process can be improved with information obtained with model-based dynamic simulation, using a Monte Carlo approach, to update a Bayesian Belief model representing the expected relations between cause and effects – and thereby produce an enhanced HAZOP. The work considers how the expertise of a hazard and operability study team might be augmented with access to behavioural models, simulations and belief inference models. This incorporates models of dynamically complex system behaviour, considering where these might contribute to the expertise of a hazard and operability study team, and how these might bolster trust in the portrayal of system behaviour. With a questionnaire containing behavioural outputs from a representative systems model, responses were collected from a group with relevant domain expertise. From this it is argued that the quality of analysis is dependent upon the experience and expertise of the participants but this might be artificially augmented using probabilistic data derived from a system dynamics model. Consequently, Monte Carlo simulations of an improved exemplar system dynamics model are used to condition a behavioural inference model and also to generate measures of emergence associated with the deviation parameter used in the study. A Bayesian approach towards probability is adopted where particular events and combinations of circumstances are effectively unique or hypothetical, and perhaps irreproducible in practice. Therefore, it is shown that a Bayesian model, representing beliefs expressed in a hazard and operability study, conditioned by the likely occurrence of flaw events causing specific deviant behaviour from evidence observed in the system dynamical behaviour, may combine intuitive estimates based upon experience and expertise, with quantitative statistical information representing plausible evidence of safety constraint violation. A further behavioural measure identifies potential emergent behaviour by way of a Lyapunov Exponent. Together these improvements enhance the awareness of potential hazard cases

Social work with airports passengers

Social work at the airport is in to offer to passengers social services. The main methodological position is that people are under stress, which characterized by a particular set of characteristics in appearance and behavior. In such circumstances passenger attracts in his actions some attention. Only person whom he trusts can help him with the documents or psychologically

A10 – Human Factors Considerations of UAS Procedures and Control Stations: Tasks PC-1 through PC-3 Pilot and Crew (PC) Subtask, Recommended Requirements and Operational Procedures

The Alliance for System Safety of UAS through Research Excellence (ASSURE) conducted research focused on minimum pilot procedures and operational practices used by unmanned aircraft systems (UAS) operators today for the purpose of developing recommendations. This research recommends four pilot and 46 operational minimum procedures to operate a civil single-engine, fixed-wing, single-pilot-configured UAS flying in beyond visual line-of-sight (BVLOS) conditions. These recommendations are anticipated to support potential future aircrew procedure requirements for UAS larger than 55 lbs. operating in the National Airspace System (NAS). These procedures were validated using representative Control Stations in simulated environments

The Need for Accelerated Integration of the Multifunctional Information Distribution System in the FA-18C Hornet

The FA-18 Hornet is a fourth-generation, supersonic, multi-role aircraft designed and built by the Boeing Aircraft Company, primarily for use as a single-seat US Navy and Marine Corps carrier-based strike/fighter. The Hornet has also been successful in the dual seat variant as both a trainer, and as a land-based aircraft for the Marines. All A through D variants have been marketed internationally as well. While the newer “E” and “F” variants are significantly different from the A through D variants in size and range and endurance capabilities, the avionics suites and capabilities are nearly identical. Except where noted, discussions of operations and aircraft/aircrew workload refer to single seat operation, as that is the majority of the combat operation of the FA-18s currently in the inventory. The purpose of this study was to examine the need (from specific operational experience) in the single seat FA-18 for a jam resistant, long range, high bandwidth datalink for the Strike mission, and how the Multifunctional Information Distribution System (MIDS) and its integration into the Hornet can fill that need. The author‘s operational analysis was done primarily on personal notes and observations during combat operations in Afghanistan October through December of 2001 and combat operations in Operation Iraqi Freedom from February through April of 2003. The capabilities and limitations of the current LINK-4 system in the FA-18, the newer Digital Communication System’s Variable Message Format and finally the MIDS/LINK-16 systems were considered, along with difficulties of MIDS integration into the current FA- 18. This analysis was done partially on data and experience obtained as the Project Officer assigned to the MIDS program, however all conclusions and recommendations are independent of the test program