Risk perception and the public acceptance of drones

Unmanned aircraft, or drones, are a rapidly emerging sector of the aviation industry. There has been limited substantive research, however, into the public perception and acceptance of drones. This paper presents the results from two surveys of the Australian public designed to investigate (a) whether the public perceive drones to be riskier than existing manned aviation, (b) whether the terminology used to describe the technology influences public perception, and (c) what the broader concerns are that may influence public acceptance of the technology. We find that the Australian public currently hold a relatively neutral attitude towards drones. Respondents did not consider the technology to be overly unsafe, risky, beneficial, or threatening. Drones are largely viewed as being of comparable risk to that of existing manned aviation. Further, terminology had a minimal effect on the perception of the risks or acceptability of the technology. The neutral response is likely due to a lack of knowledge about the technology, which was also identified as the most prevalent public concern as opposed to the risks associated with its use. Privacy, military use and misuse (e.g., terrorism) were also significant public concerns. The results suggest that society is yet to form an opinion of drones. As public knowledge increases, the current position is likely to change. Industry communication and media coverage will likely influence the ultimate position adopted by the public, which can be difficult to change once established.

Design, modelling and measurement of a hybrid powerplant for unmanned aerial systems

Hybrid powerplants combining internal combustion engines and electric motor prime movers have been extensively developed for land- and marine-based transport systems. The use of such powerplants in airborne applications has been historically impractical due to energy and power density constraints. Improvements in battery and electric motor technology make aircraft hybrid powerplants feasible. This paper presents a technique for determining the feasibility and mechanical effectiveness of powerplant hybridisation. In this work, a prototype aircraft hybrid powerplant was designed, constructed and tested. It is shown that an additional 35% power can be supplied from the hybrid system with an overall weight penalty of 5%, for a given unmanned aerial system. A flight dynamic model was developed using the AeroSim Blockset in MATLAB Simulink. The results have shown that climb rates can be improved by 56% and endurance increased by 13% when using the hybrid powerplant concept.

Flying robots to the rescue

UAVs could one day save the lives of lost civilians and those sent to find them, and a competition in outback Australia is proving how soon that day might come. We have all seen news stories of people who ventured beyond the day-to-day reach of the community and got lost: search parties are formed, aircraft drafted in, and often large sums of money expended in the quest to find them.

The effect of autonomy transparency in human-robot interactions : a preliminary study on operator cognitive workload and situation awareness in multiple heterogeneous UAV management

The autonomous capabilities in collaborative unmanned aircraft systems are growing rapidly. Without appropriate transparency, the effectiveness of the future multiple Unmanned Aerial Vehicle (UAV) management paradigm will be significantly limited by the human agent’s cognitive abilities; where the operator’s CognitiveWorkload (CW) and Situation Awareness (SA) will present as disproportionate. This proposes a challenge in evaluating the impact of robot autonomous capability feedback, allowing the human agent greater transparency into the robot’s autonomous status - in a supervisory role. This paper presents; the motivation, aim, related works, experiment theory, methodology, results and discussions, and the future work succeeding this preliminary study. The results in this paper illustrates that, with a greater transparency of a UAV’s autonomous capability, an overall improvement in the subjects’ cognitive abilities was evident, that is, with a confidence of 95%, the test subjects’ mean CW was demonstrated to have a statistically significant reduction, while their mean SA was demonstrated to have a significant increase.

Modeling and control of a robotic power line inspection vehicle

Power line inspection is a vital function for electricity supply companies but it involves labor-intensive and expensive procedures which are tedious and error-prone for humans to perform. A possible solution is to use an unmanned aerial vehicle (UAV) equipped with video surveillance equipment to perform the inspection. This paper considers how a small, electrically driven rotorcraft conceived for this application could be controlled by visually tracking the overhead supply lines. A dynamic model for a ducted-fan rotorcraft is presented and used to control the action of an Air Vehicle Simulator (AVS), consisting of a cable-array robot. Results show how visual data can be used to determine, and hence regulate in closed loop, the simulated vehicle’s position relative to the overhead lines.

Agent-based modelling and simulation of airplane boarding processes

Passenger flow simulations are an important tool for designing and managing airports. This thesis examines the different boarding strategies for the Boeing 777 and Airbus 380 aircraft in order to investigate their current performance and to determine minimum boarding times. The most optimal strategies have been discovered and new strategies that are more efficient are proposed. The methods presented offer reduced aircraft boarding times which plays an important role for reducing the overall aircraft Turn Time for an airline.

3D reconfigurable autopilot flight system for both general aviation and unmanned aerial systems

This research project investigated and designed a modular architecture for a 3D Reconfigurable Autopilot Flight System that could be used to control actuators in both manned and unmanned aircraft. The system is based on a CAN Bus interface and allows seamless control of different types of actuators. During the course of the research the differences and similarities of autopilots for fixed-wing general aviation aircraft and unmanned aircraft were analysed focusing on the actuator interfaces. This project suggests that software and hardware used in commercial-of-the-shelf avionics could be used in manned and unmanned aviation.

Flight-training effect on the cervical muscle isometric strength of trainee pilots

External stimulus/loading initiates adaptations within skeletal muscle. It has been previously found that the cervical area has the highest loading while performing flying maneuvers under +Gz. The first purpose of this study was to examine the neck muscle response to the physical environment associated with flight training, incorporating limited exposure to +Gz force, in a Pilatus PC-9 aircraft. The second purpose was to examine the short-term range of movement (ROM) response to flight training. Isometric cervical muscle strength and ROM was monitored in 9 RAAF pilots completing an 8-mo flight-training course at Pearce Airbase in Western Australia, and in 10 controls matched for gender, age, height, and weight. Isometric cervical muscle strength and ROM were measured at baseline and at 8 mo using the multi-cervical rehabilitation unit (Hanoun Medical, Downsview, Ontario, Canada). Results indicated that an increase in pilot neck strength was limited to flexion while in a neutral position. No strength changes were recorded in any other site in the pilots or for the controls. These findings suggest that short-term exposure to the physical environment associated with flight training had a limited significant effect on increasing isometric cervical muscle strength. No significant changes were observed in pilot ROM, indicating that short-term exposure to flight does not effect ROM.

Evolutionary optimization and game strategies for advanced multi-disciplinary design : applications to aeronautics and UAV design

Many complex aeronautical design problems can be formulated with efficient multi-objective evolutionary optimization methods and game strategies. This book describes the role of advanced innovative evolution tools in the solution, or the set of solutions of single or multi disciplinary optimization. These tools use the concept of multi-population, asynchronous parallelization and hierarchical topology which allows different models including precise, intermediate and approximate models with each node belonging to the different hierarchical layer handled by a different Evolutionary Algorithm. The efficiency of evolutionary algorithms for both single and multi-objective optimization problems are significantly improved by the coupling of EAs with games and in particular by a new dynamic methodology named “Hybridized Nash-Pareto games”. Multi objective Optimization techniques and robust design problems taking into account uncertainties are introduced and explained in detail. Several applications dealing with civil aircraft and UAV, UCAV systems are implemented numerically and discussed. Applications of increasing optimization complexity are presented as well as two hands-on test cases problems. These examples focus on aeronautical applications and will be useful to the practitioner in the laboratory or in industrial design environments. The evolutionary methods coupled with games presented in this volume can be applied to other areas including surface and marine transport, structures, biomedical engineering, renewable energy and environmental problems.

Multi-rotor with suspended load: System dynamics and control toolbox

There is an increasing demand for Unmanned Aerial Systems (UAS) to carry suspended loads as this can provide significant benefits to several applications in agriculture, law enforcement and construction. The load impact on the underlying system dynamics should not be neglected as significant feedback forces may be induced on the vehicle during certain flight manoeuvres. The constant variation in operating point induced by the slung load also causes conventional controllers to demand increased control effort. Much research has focused on standard multi-rotor position and attitude control with and without a slung load. However, predictive control schemes, such as Nonlinear Model Predictive Control (NMPC), have not yet been fully explored. To this end, we present a novel controller for safe and precise operation of multi-rotors with heavy slung load in three dimensions. The paper describes a System Dynamics and Control Simulation Toolbox for use with MATLAB/SIMULINK which includes a detailed simulation of the multi-rotor and slung load as well as a predictive controller to manage the nonlinear dynamics whilst accounting for system constraints. It is demonstrated that the controller simultaneously tracks specified waypoints and actively damps large slung load oscillations. A linear-quadratic regulator (LQR) is derived and control performance is compared. Results show the improved performance of the predictive controller for a larger flight envelope, including aggressive manoeuvres and large slung load displacements. The computational cost remains relatively small, amenable to practical implementations.

Design and evaluation of decision and control strategies for autonomous vision-based see and avoid systems

This paper details the design and performance assessment of a unique collision avoidance decision and control strategy for autonomous vision-based See and Avoid systems. The general approach revolves around re-positioning a collision object in the image using image-based visual servoing, without estimating range or time to collision. The decision strategy thus involves determining where to move the collision object, to induce a safe avoidance manuever, and when to cease the avoidance behaviour. These tasks are accomplished by exploiting human navigation models, spiral motion properties, expected image feature uncertainty and the rules of the air. The result is a simple threshold based system that can be tuned and statistically evaluated by extending performance assessment techniques derived for alerting systems. Our results demonstrate how autonomous vision-only See and Avoid systems may be designed under realistic problem constraints, and then evaluated in a manner consistent to aviation expectations.

Online hidden Markov model parameter estimation and minimax robust quickest change detection in uncertain stochastic processes

Stochastic (or random) processes are inherent to numerous fields of human endeavour including engineering, science, and business and finance. This thesis presents multiple novel methods for quickly detecting and estimating uncertainties in several important classes of stochastic processes. The significance of these novel methods is demonstrated by employing them to detect aircraft manoeuvres in video signals in the important application of autonomous mid-air collision avoidance.

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Effect of ion nitriding on the microstructure and properties of Maraging steel (250 Grade)

In the present investigation, ion nitriding of Maraging steel (250 grade) has been carried out at three different temperatures i.e., at 435 degrees C, 450 degrees C and 465 degrees C for 10 h duration in order to achieve good wear resistance along with high strength required for the slat track component of aircraft. The microstructure of the base material and the nitrided layer was examined by optical and scanning electron microscope, and various phases present were determined by X-ray diffraction. Various properties, such as, hardness, case depth, tensile, impact, fatigue properties and corrosion resistance were investigated for both un-nitrided and ion-nitrided materials. It is observed that the microstructure of the core material remains unaltered and Fe4N is formed in the hardened surface layer after ion nitriding at all the three temperatures employed. Surface hardness increases substantially after ion nitriding. Surface hardness remains almost the same but case depth increases with the increase in ion nitriding temperature due to greater diffusivity at higher temperatures. Tensile strength, fatigue strength and corrosion resistance are improved but ductility and energy absorbed in impact test decrease on ion nitriding. These results are explained on the basis of microstructural observations. The properties obtained after ion nitriding at 450 degrees C for 10 h are found to be optimum when compared to the other two ion nitriding temperatures.