Risk-management of UAS robust autonomy for its integration into civil aviation safety frameworks

This paper discusses a model of the civil aviation reg- ulation framework and shows how the current assess- ment of reliability and risk for piloted aircraft has limited applicability for Unmanned Aircraft Systems (UAS) with high levels of autonomous decision mak- ing. Then, a new framework for risk management of robust autonomy is proposed, which arises from combining quantified measures of risk with normative decision making. The term Robust Autonomy de- scribes the ability of an autonomous system to either continue or abort its operation whilst not breaching a minimum level of acceptable safety in the presence of anomalous conditions. The decision making associ- ated with risk management requires quantifying prob- abilities associated with the measures of risk and also consequences of outcomes related to the behaviour of autonomy. The probabilities are computed from an assessment under both nominal and anomalous sce- narios described by faults, which can be associated with the aircraft���s actuators, sensors, communication link, changes in dynamics, and the presence of other aircraft in the operational space. The consequences of outcomes are characterised by a loss function which rewards the certification decision

Evaluation of robust autonomy and implications on UAS certification and design

As the number of potential applications of Unmanned Aircraft Systems (UAS) grows in civilian operations and national security, National Airworthiness Authorities are under increasing pressure to provide a path for certification and allow UAS integration into the national airspace. The success of this integration depends on developments in improved UAS reliability and safety, regulations for certification, and technologies for operational performance and safety assessment. This paper focusses on the latter and describes the use of a framework for evaluating robust autonomy of UAS, namely, the autonomous system’s ability to either continue operation in the presence of faults or safely shut down. The paper draws parallels between the proposed evaluation framework and the evaluation of pilots during the licensing process. It also discusses how the data from the proposed evaluation can be uses as an aid for decision making in certification and UAS designs.

Computational aspects of probabilistic assessment of UAS robust autonomy

As the level of autonomy in Unmanned Aircraft Systems (UAS) increases, there is an imperative need for developing methods to assess robust autonomy. This paper focuses on the computations that lead to a set of measures of robust autonomy. These measures are the probabilities that selected performance indices related to the mission requirements and airframe capabilities remain within regions of acceptable performance.

Management of multiple heterogeneous UAVs using capability and autonomy visualisation: theory, experiment and result

The interest in utilising multiple heterogeneous Unmanned Aerial Vehicles (UAVs) in close proximity is growing rapidly. As such, many challenges are presented in the effective coordination and management of these UAVs; converting the current n-to-1 paradigm (n operators operating a single UAV) to the 1-to-n paradigm (one operator managing n UAVs). This paper introduces an Information Abstraction methodology used to produce the functional capability framework initially proposed by Chen et al. and its Level Of Detail (LOD) indexing scale. This framework was validated through comparing the operator workload and Situation Awareness (SA) of three experiment scenarios involving multiple autonomously heterogeneous UAVs. The first scenario was set in a high LOD configuration with highly abstracted UAV functional information; the second scenario was set in a mixed LOD configuration; and the final scenario was set in a low LOD configuration with maximal UAV functional information. Results show that there is a significant statistical decrease in operator workload when a UAV’s functional information is displayed at its physical form (low LOD - maximal information) when comparing to the mixed LOD configuration.

Joint motion control and control allocation design for UAS flight control systems

As Unmanned Aircraft Systems (UAS) grow in complexity, and their level of autonomy increases|moving away from the concept of a remotely piloted systems and more towards autonomous systems|there is a need to further improve reliability and tolerance to faults. The traditional way to accommodate actuator faults is by using standard control allocation techniques as part of the flight control system. The allocation problem in the presence of faults often requires adding constraints that quantify the maximum capacity of the actuators. This in turn requires on-line numerical optimisation. In this paper, we propose a framework for joint allocation and constrained control scheme via vector input scaling. The actuator configuration is used to map actuator constraints into the space of the aircraft generalised forces, which are the magnitudes demanded by the light controller. Then by constraining the output of controller, we ensure that the allocation function always receive feasible demands. With the proposed framework, the allocation problem does not require numerical optimisation, and since the controller handles the constraints, there is not need to implement heuristics to inform the controller about actuator saturation.

Parameter estimation of thrust models of uninhabited airborne systems

This paper presents a method for the estimation of thrust model parameters of uninhabited airborne systems using specific flight tests. Particular tests are proposed to simplify the estimation. The proposed estimation method is based on three steps. The first step uses a regression model in which the thrust is assumed constant. This allows us to obtain biased initial estimates of the aerodynamic coeficients of the surge model. In the second step, a robust nonlinear state estimator is implemented using the initial parameter estimates, and the model is augmented by considering the thrust as random walk. In the third step, the estimate of the thrust obtained by the observer is used to fit a polynomial model in terms of the propeller advanced ratio. We consider a numerical example based on Monte-Carlo simulations to quantify the sampling properties of the proposed estimator given realistic flight conditions.

Recursive actuator fault detection and diagnosis for emergency landing of UASs

This paper presents a practical recursive fault detection and diagnosis (FDD) scheme for online identification of actuator faults for unmanned aerial systems (UASs) based on the unscented Kalman filtering (UKF) method. The proposed FDD algorithm aims to monitor health status of actuators and provide indication of actuator faults with reliability, offering necessary information for the design of fault-tolerant flight control systems to compensate for side-effects and improve fail-safe capability when actuator faults occur. The fault detection is conducted by designing separate UKFs to detect aileron and elevator faults using a nonlinear six degree-of-freedom (DOF) UAS model. The fault diagnosis is achieved by isolating true faults by using the Bayesian Classifier (BC) method together with a decision criterion to avoid false alarms. High-fidelity simulations with and without measurement noise are conducted with practical constraints considered for typical actuator fault scenarios, and the proposed FDD exhibits consistent effectiveness in identifying occurrence of actuator faults, verifying its suitability for integration into the design of fault-tolerant flight control systems for emergency landing of UASs.

Towards the development of 1-to-n human machine interfaces for unmanned aerial vehicles

Multi-touch interfaces across a wide range of hardware platforms are becoming pervasive. This is due to the adoption of smart phones and tablets in both the consumer and corporate market place. This paper proposes a human-machine interface to interact with unmanned aerial systems based on the philosophy of multi-touch hardware-independent high-level interaction with multiple systems simultaneously. Our approach incorporates emerging development methods for multi-touch interfaces on mobile platforms. A framework is defined for supporting multiple protocols. An open source solution is presented that demonstrates: architecture supporting different communications hardware; an extensible approach for supporting multiple protocols; and the ability to monitor and interact with multiple UAVs from multiple clients simultaneously. Validation tests were conducted to assess the performance, scalability and impact on packet latency under different client configurations.

Agent-based application on different boarding strategies

In this paper we implemented six different boarding strategies (Wilma, Steffen, Reverse Pyramid, Random, Blocks and By letter) in order to minimize boarding time and turnaround time for Boeing 777 and Airbus 380 aircrafts by using Agent-based modelling approach. In the simulation, we divided passengers into six different categories which are group size more than 5 people, passengers with child, gold members, first class passengers, business class passengers and economy class passengers. Results from the simulation demonstrates Reverse Pyramid method is the best boarding method for Boeing 777 and Steffen method is the best boarding method for Airbus 380.

Non-linear model predictive control for UAVs with slung/swung load

Suspended loads on UAVs 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. 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 software and flight system architecture to test controller for safe and precise operation of multi-rotors with heavy slung load in three dimensions.

High-frequency global navigation satellite system’s receivers for airborne gravimetry

The development of global navigation satellite systems (GNSS) provides a solution of many applied problems with increasingly higher quality and accuracy nowadays. Researches that are carried out by the Bavarian Academy of Sciences and Humanities in Munich (BAW) in the field of airborne gravimetry are based on sophisticated data processing from high frequency GNSS receiver for kinematic aircraft positioning. Applied algorithms for inertial acceleration determination are based on the high sampling rate (50Hz) and on reducing of such factors as ionosphere scintillation and multipath at aircraft /antenna near field effects. The quality of the GNSS derived kinematic height are studied also by intercomparison with lift height variations collected by a precise high sampling rate vertical scale [1]. This work is aimed at the ways of more accurate determination of mini-aircraft altitude by means of high frequency GNSS receivers, in particular by considering their dynamic behaviour.

Design methodologies and architectures of hardware-based evolutionary algorithms for aerospace optimisation applications on FPGAS

This thesis is a study of new design methods for allowing evolutionary algorithms to be more effectively utilised in aerospace optimisation applications where computation needs are high and computation platform space may be restrictive. It examines the applicability of special hardware computational platforms known as field programmable gate arrays and shows that with the right implementation methods they can offer significant benefits. This research is a step forward towards the advancement of efficient and highly automated aircraft systems for meeting compact physical constraints in aerospace platforms and providing effective performance speedups over traditional methods.

Построение автоматической навигационной системы малогабаритного беспилотного летательного аппарата многократного применения = Development of automatic navigation management system for small unmanned aerial vehicle

Современный этап развития комплексов автоматического управления и навигации малогабаритными БЛА многократного применения предъявляет высокие требования к автономности, точности и миниатюрности данных систем. Противоречивость требований диктует использование функционального и алгоритмического объединения нескольких разнотипных источников навигационной информации в едином вычислительном процессе на основе методов оптимальной фильтрации. Получили широкое развитие бесплатформенные инерциальные навигационные системы (БИНС) на основе комплексирования данных микромеханических датчиков инерциальной информации и датчиков параметров движения в воздушном потоке с данными спутниковых навигационных систем (СНС). Однако в современных условиях такой подход не в полной мере реализует требования к помехозащищённости, автономности и точности получаемой навигационной информации. Одновременно с этим достигли значительного прогресса навигационные системы, использующие принципы корреляционно экстремальной навигации по оптическим ориентирам и цифровым картам местности. Предлагается схема построения автономной автоматической навигационной системы (АНС) для БЛА многоразового применения на основе объединения алгоритмов БИНС, спутниковой навигационной системы и оптической навигационной системы. The modern stage of automatic control and guidance systems development for small unmanned aerial vehicles (UAV) is determined by advanced requirements for autonomy, accuracy and size of the systems. The contradictory of the requirements dictates novel functional and algorithmic tight coupling of several different onboard sensors into one computational process, which is based on methods of optimal filtering. Nowadays, data fusion of micro-electro mechanical sensors of inertial measurement units, barometric pressure sensors, and signals of global navigation satellite systems (GNSS) receivers is widely used in numerous strap down inertial navigation systems (INS). However, the systems do not fully comply with such requirements as jamming immunity, fault tolerance, autonomy, and accuracy of navigation. At the same time, the significant progress has been recently demonstrated by the navigation systems, which use the correlation extremal principle applied for optical data flow and digital maps. This article proposes a new architecture of automatic navigation management system (ANMS) for small UAV, which combines algorithms of strap down INS, satellite navigation and optical navigation system.

Исследования и испытания алгоритмов автоматической пилотажно-навигационной системы малогабаритного беспилотного летательного аппарата = Research and testing of automatic navigation management system’s algorithms for small unmanned aerial vehicle

В статье представлено развитие принципа построения автоматической пилотажно-навигационной системы (АПНС) для беспилотного летательного аппарата (БЛА). Принцип заключается в синтезе комплексных систем управления БПЛА не только на основе использования алгоритмов БИНС, но и алгоритмов, объединяющих в себе решение задач формирования и отработки сформированной траектории резервированной системой управления и навигации. Приведены результаты аналитического исследования и данные летных экспериментов разработанных алгоритмов АПНС БЛА, обеспечивающих дополнительное резервирование алгоритмов навигации и наделяющих БЛА новым функциональной способностью по выходу в заданную точку пространства с заданной скоростью в заданный момент времени с учетом атмосферных ветровых возмущений. Предложена и испытана методика идентификации параметров воздушной атмосферы: направления и скорости W ветра. Данные летных испытаний полученного решения задачи терминальной навигации демонстрируют устойчивую работу синтезированных алгоритмов управления в различных метеоусловиях. The article presents a progress in principle of development of automatic navigation management system (ANMS) for small unmanned aerial vehicle (UAV). The principle defines a development of integrated control systems for UAV based on tight coupling of strap down inertial navigation system algorithms and algorithms of redundant flight management system to form and control flight trajectory. The results of the research and flight testing of the developed ANMS UAV algorithms are presented. The system demonstrates advanced functional redundancy of UAV guidance. The system enables new UAV capability to perform autonomous multidimensional navigation along waypoints with controlled speed and time of arrival taking into account wind. The paper describes the technique for real-time identification of atmosphere parameters such as wind direction and wind speed. The flight test results demonstrate robustness of the algorithms in diverse meteorological conditions.

Decision strategies for automated visual collision avoidance

This paper provides a preliminary analysis of an autonomous uncooperative collision avoidance strategy for unmanned aircraft using image-based visual control. Assuming target detection, the approach consists of three parts. First, a novel decision strategy is used to determine appropriate reference image features to track for safe avoidance. This is achieved by considering the current rules of the air (regulations), the properties of spiral motion and the expected visual tracking errors. Second, a spherical visual predictive control (VPC) scheme is used to guide the aircraft along a safe spiral-like trajectory about the object. Lastly, a stopping decision based on thresholding a cost function is used to determine when to stop the avoidance behaviour. The approach does not require estimation of range or time to collision, and instead relies on tuning two mutually exclusive decision thresholds to ensure satisfactory performance.