Automating human thought processes for a UAV forced landing

This paper describes the current status of a program to develop an automated forced landing system for a fixed-wing Unmanned Aerial Vehicle (UAV). This automated system seeks to emulate human pilot thought processes when planning for and conducting an engine-off emergency landing. Firstly, a path planning algorithm that extends Dubins curves to 3D space is presented. This planning element is then combined with a nonlinear guidance and control logic, and simulated test results demonstrate the robustness of this approach to strong winds during a glided descent. The average path deviation errors incurred are comparable to or even better than that of manned, powered aircraft. Secondly, a study into suitable multi-criteria decision making approaches and the problems that confront the decision-maker is presented. From this study, it is believed that decision processes that utilize human expert knowledge and fuzzy logic reasoning are most suited to the problem at hand, and further investigations will be conducted to identify the particular technique/s to be implemented in simulations and field tests. The automated UAV forced landing approach presented in this paper is promising, and will allow the progression of this technology from the development and simulation stages through to a prototype system

Guided chaos : path planning and control for a UAV-forced landing

In recent years, unmanned aerial vehicles (UAVs) have been widely used in combat, and their potential applications in civil and commercial roles are also receiving considerable attention by industry and the research community. There are numerous published reports of UAVs used in Earth science missions [1], fire-fighting [2], and border security [3] trials, with other speculative deployments, including applications in agriculture, communications, and traffic monitoring. However, none of these UAVs can demonstrate an equivalent level of safety to manned aircraft, particularly in the case of an engine failure, which would require an emergency or forced landing. This may be arguably the main factor that has prevented these UAV trials from becoming full-scale commercial operations, as well as restricted operations of civilian UAVs to only within segregated airspace.

Distinguishing forced versus discretionary replacements in new product diffusion models

In many product categories of durable goods such as TV, PC, and DVD player, the largest component of sales is generated by consumers replacing existing units. Aggregate sales models proposed by diffusion of innovation researchers for the replacement component of sales have incorporated several different replacement distributions such as Rayleigh, Weibull, Truncated Normal and Gamma. Although these alternative replacement distributions have been tested using both time series sales data and individual-level actuarial “life-tables” of replacement ages, there is no census on which distributions are more appropriate to model replacement behaviour. In the current study we are motivated to develop a new “modified gamma” distribution by two reasons. First we recognise that replacements have two fundamentally different drivers – those forced by failure and early, discretionary replacements. The replacement distribution for each of these drivers is expected to be quite different. Second, we observed a poor fit of other distributions to out empirical data. We conducted a survey of 8,077 households to empirically examine models of replacement sales for six electronic consumer durables – TVs, VCRs, DVD players, digital cameras, personal and notebook computers. This data allows us to construct individual-level “life-tables” for replacement ages. We demonstrate the new modified gamma model fits the empirical data better than existing models for all six products using both a primary and a hold-out sample.

Forced landing technologies for unmanned aerial vehicles : towards safer operations

While using unmanned systems in combat is not new, what will be new in the foreseeable future is how such systems are used and integrated in the civilian space. The potential use of Unmanned Aerial Vehicles in civil and commercial applications is becoming a fact, and is receiving considerable attention by industry and the research community. The majority of Unmanned Aerial Vehicles performing civilian tasks are restricted to flying only in segregated space, and not within the National Airspace. The areas that UAVs are restricted to flying in are typically not above populated areas, which in turn are the areas most useful for civilian applications. The reasoning behind the current restrictions is mainly due to the fact that current UAV technologies are not able to demonstrate an Equivalent Level of Safety to manned aircraft, particularly in the case of an engine failure which would require an emergency or forced landing. This chapter will preset and guide the reader through a number of developments that would facilitate the integration of UAVs into the National Airspace. Algorithms for UAV Sense-and-Avoid and Force Landings are recognized as two major enabling technologies that will allow the integration of UAVs in the civilian airspace. The following sections will describe some of the techniques that are currently being tested at the Australian Research Centre for Aerospace Automation (ARCAA), which places emphasis on the detection of candidate landing sites using computer vision, the planning of the descent path trajectory for the UAV, and the decision making process behind the selection of the final landing site.

Path planning, guidance and control for a UAV forced landing

A forced landing is an unscheduled event in flight requiring an emergency landing, and is most commonly attributed to engine failure, failure of avionics or adverse weather. Since the ability to conduct a successful forced landing is the primary indicator for safety in the aviation industry, automating this capability for unmanned aerial vehicles (UAVs) will help facilitate their integration into, and subsequent routine operations over civilian airspace. Currently, there is no commercial system available to perform this task; however, a team at the Australian Research Centre for Aerospace Automation (ARCAA) is working towards developing such an automated forced landing system. This system, codenamed Flight Guardian, will operate onboard the aircraft and use machine vision for site identification, artificial intelligence for data assessment and evaluation, and path planning, guidance and control techniques to actualize the landing. This thesis focuses on research specific to the third category, and presents the design, testing and evaluation of a Trajectory Generation and Guidance System (TGGS) that navigates the aircraft to land at a chosen site, following an engine failure. Firstly, two algorithms are developed that adapts manned aircraft forced landing techniques to suit the UAV planning problem. Algorithm 1 allows the UAV to select a route (from a library) based on a fixed glide range and the ambient wind conditions, while Algorithm 2 uses a series of adjustable waypoints to cater for changing winds. A comparison of both algorithms in over 200 simulated forced landings found that using Algorithm 2, twice as many landings were within the designated area, with an average lateral miss distance of 200 m at the aimpoint. These results present a baseline for further refinements to the planning algorithms. A significant contribution is seen in the design of the 3-D Dubins Curves planning algorithm, which extends the elementary concepts underlying 2-D Dubins paths to account for powerless flight in three dimensions. This has also resulted in the development of new methods in testing for path traversability, in losing excess altitude, and in the actual path formation to ensure aircraft stability. Simulations using this algorithm have demonstrated lateral and vertical miss distances of under 20 m at the approach point, in wind speeds of up to 9 m/s. This is greater than a tenfold improvement on Algorithm 2 and emulates the performance of manned, powered aircraft. The lateral guidance algorithm originally developed by Park, Deyst, and How (2007) is enhanced to include wind information in the guidance logic. A simple assumption is also made that reduces the complexity of the algorithm in following a circular path, yet without sacrificing performance. Finally, a specific method of supplying the correct turning direction is also used. Simulations have shown that this new algorithm, named the Enhanced Nonlinear Guidance (ENG) algorithm, performs much better in changing winds, with cross-track errors at the approach point within 2 m, compared to over 10 m using Park's algorithm. A fourth contribution is made in designing the Flight Path Following Guidance (FPFG) algorithm, which uses path angle calculations and the MacCready theory to determine the optimal speed to fly in winds. This algorithm also uses proportional integral- derivative (PID) gain schedules to finely tune the tracking accuracies, and has demonstrated in simulation vertical miss distances of under 2 m in changing winds. A fifth contribution is made in designing the Modified Proportional Navigation (MPN) algorithm, which uses principles from proportional navigation and the ENG algorithm, as well as methods specifically its own, to calculate the required pitch to fly. This algorithm is robust to wind changes, and is easily adaptable to any aircraft type. Tracking accuracies obtained with this algorithm are also comparable to those obtained using the FPFG algorithm. For all three preceding guidance algorithms, a novel method utilising the geometric and time relationship between aircraft and path is also employed to ensure that the aircraft is still able to track the desired path to completion in strong winds, while remaining stabilised. Finally, a derived contribution is made in modifying the 3-D Dubins Curves algorithm to suit helicopter flight dynamics. This modification allows a helicopter to autonomously track both stationary and moving targets in flight, and is highly advantageous for applications such as traffic surveillance, police pursuit, security or payload delivery. Each of these achievements serves to enhance the on-board autonomy and safety of a UAV, which in turn will help facilitate the integration of UAVs into civilian airspace for a wider appreciation of the good that they can provide. The automated UAV forced landing planning and guidance strategies presented in this thesis will allow the progression of this technology from the design and developmental stages, through to a prototype system that can demonstrate its effectiveness to the UAV research and operations community.

A forced titration study of the antioxidant and immunomodulatory effects of Ambrotose AO supplement

Background Oxidative stress plays a role in acute and chronic inflammatory disease and antioxidant supplementation has demonstrated beneficial effects in the treatment of these conditions. This study was designed to determine the optimal dose of an antioxidant supplement in healthy volunteers to inform a Phase 3 clinical trial. Methods The study was designed as a combined Phase 1 and 2 open label, forced titration dose response study in healthy volunteers (n = 21) to determine both acute safety and efficacy. Participants received a dietary supplement in a forced titration over five weeks commencing with a no treatment baseline through 1, 2, 4 and 8 capsules. The primary outcome measurement was ex vivo changes in serum oxygen radical absorbance capacity (ORAC). The secondary outcome measures were undertaken as an exploratory investigation of immune function. Results A significant increase in antioxidant activity (serum ORAC) was observed between baseline (no capsules) and the highest dose of 8 capsules per day (p = 0.040) representing a change of 36.6%. A quadratic function for dose levels was fitted in order to estimate a dose response curve for estimating the optimal dose. The quadratic component of the curve was significant (p = 0.047), with predicted serum ORAC scores increasing from the zero dose to a maximum at a predicted dose of 4.7 capsules per day and decreasing for higher doses. Among the secondary outcome measures, a significant dose effect was observed on phagocytosis of granulocytes, and a significant increase was also observed on Cox 2 expression. Conclusion This study suggests that Ambrotose AO® capsules appear to be safe and most effective at a dosage of 4 capsules/day. It is important that this study is not over interpreted; it aimed to find an optimal dose to assess the dietary supplement using a more rigorous clinical trial design. The study achieved this aim and demonstrated that the dietary supplement has the potential to increase antioxidant activity. The most significant limitation of this study was that it was open label Phase 1/Phase 2 trial and is subject to potential bias that is reduced with the use of randomization and blinding. To confirm the benefits of this dietary supplement these effects now need to be demonstrated in a Phase 3 randomised controlled trial (RCT).

Periodically forced natural convection through the roof of an attic-shaped building

In this study, numerical simulations of natural convection in an attic space subject to diurnal temperature condition on the sloping wall have been carried out. An explanation of choosing the period of periodic thermal effect has been given with help of the scaling analysis which is available in the literature. Moreover, the effects of the aspect ratio and Rayleigh number on the fluid flow and heat transfer have been discussed in details as well as the formation of a pitchfork bifurcation of the flow at the symmetric line of the enclosure.

Experimental validation of an unpowered unmanned aerial system : application to forced landing scenarios

The ability to perform autonomous emergency (forced) landings is one of the key technology enablers identified for UAS. This paper presents the flight test results of forced landings involving a UAS, in a controlled environment, and which was conducted to ascertain the performances of previously developed (and published) path planning and guidance algorithms. These novel 3-D nonlinear algorithms have been designed to control the vehicle in both the lateral and longitudinal planes of motion. These algorithms have hitherto been verified in simulation. A modified Boomerang 60 RC aircraft is used as the flight test platform, with associated onboard and ground support equipment sourced Off-the-Shelf or developed in-house at the Australian Research Centre for Aerospace Automation(ARCAA). HITL simulations were conducted prior to the flight tests and displayed good landing performance, however, due to certain identified interfacing errors, the flight results differed from that obtained in simulation. This paper details the lessons learnt and presents a plausible solution for the way forward.

Adaptive subcarrier allocation in multiuser OFDM system using forced cost based decisions

Subcarrier allocation scheme for Orthogonal Frequency Division Multiplexing(OFDM) based multiuser system is proposed. Most previous algorithms use greedy approach as a subcarrier allocation scheme until a conflict occurs or as an initial first round allocation with improvement steps carried out in next rounds. Our algorithm uses information obtained by the forced costs of a system that incur by a current allocation to make assignment decisions. This algorithm does not rely on greedy approach and therefore can also be considered as a substitute for first layer Greedy algorithms. Simulation results show that for two user case this algorithm gives better or equal allocation 80-90 percent of the time when compared with the greedy allocation.

Resource allocation in multiuser cooperative OFDM system using forced cost based decisions

A sub optimal resource allocation algorithm for Orthogonal Frequency Division Multiplexing (OFDM) based cooperative scheme is proposed. The system consists of multiple relays. Subcarrier space is divided into blocks and relays participating in cooperation are allocated specific blocks to be used with a user. To ensure unique subcarrier assignment system is constrained such that same block cannot be used by more than one user. Users are given fair block assignments while no restriction for maximum number of blocks a relay can employ is given. Forced cost based decisions [1] are used for block allocation. Simulation results show that this scheme outperforms a non cooperating scheme with sequential allocation with respect to power usage.

Dying for the bonds of marriage : forced marriages as a weapon of genocide

‘Forced marriages’ involve a woman or girl being abducted and declared the ‘wife’ of her captor without her consent or her family’s consent. The practice generally occurs during wartime and the ‘wife’ is normally subjected to rape, forced impregnation and sexual slavery. Moreover, she is coerced into an intimate relationship with a man who is often the perpetrator of crimes against her and her community. While forced marriages have recently been recognised as a crime against humanity, this Article contends that this does not constitute full recognition of the destructive nature of forced marriages. Instead, this Article mirrors and extends the Akayesu decision that rape can be used as a tool of genocide and maintains that forced marriages can also be a form of genocide.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the a mission should be aborted due to mechanical or other failure. On-board cameras provide information that can be used in the determination of potential landing sites, which are continually updated and ranked to prevent injury and minimize damage. Pulse Coupled Neural Networks have been used for the detection of features in images that assist in the classification of vegetation and can be used to minimize damage to the aerial vehicle. However, a significant drawback in the use of PCNNs is that they are computationally expensive and have been more suited to off-line applications on conventional computing architectures. As heterogeneous computing architectures are becoming more common, an OpenCL implementation of a PCNN feature generator is presented and its performance is compared across OpenCL kernels designed for CPU, GPU and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images obtained during unmanned aerial vehicle trials to determine the plausibility for real-time feature detection.

Autonomous forced landing system for light general aviation aircraft in unknown environments

This paper presents a system which enhances the capabilities of a light general aviation aircraft to land autonomously in case of an unscheduled event such as engine failure. The proposed system will not only increase the level of autonomy for the general aviation aircraft industry but also increase the level of dependability. Safe autonomous landing in case of an engine failure with a certain level of reliability is the primary focus of our work as both safety and reliability are attributes of dependability. The system is designed for a light general aviation aircraft but can be extended for dependable unmanned aircraft systems. The underlying system components are computationally efficient and provides continuous situation assessment in case of an emergency landing. The proposed system is undergoing an evaluation phase using an experimental platform (Cessna 172R) in real world scenarios.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the mission should be aborted due to mechanical or other failure. This article presents a pulse-coupled neural network (PCNN) to assist in the vegetation classification in a vision-based landing site detection system for an unmanned aircraft. We propose a heterogeneous computing architecture and an OpenCL implementation of a PCNN feature generator. Its performance is compared across OpenCL kernels designed for CPU, GPU, and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images to determine the plausibility for real-time feature detection.