A synthesizable hardware evolutionary algorithm design for unmanned aerial system real-time path planning

The main objective of this paper is to detail the development of a feasible hardware design based on Evolutionary Algorithms (EAs) to determine flight path planning for Unmanned Aerial Vehicles (UAVs) navigating terrain with obstacle boundaries. The design architecture includes the hardware implementation of Light Detection And Ranging (LiDAR) terrain and EA population memories within the hardware, as well as the EA search and evaluation algorithms used in the optimizing stage of path planning. A synthesisable Very-high-speed integrated circuit Hardware Description Language (VHDL) implementation of the design was developed, for realisation on a Field Programmable Gate Array (FPGA) platform. Simulation results show significant speedup compared with an equivalent software implementation written in C++, suggesting that the present approach is well suited for UAV real-time path planning applications.

A multi-resolution image alignment technique based on direct methods for pose estimation of aerial vehicles

In this paper, we seek to expand the use of direct methods in real-time applications by proposing a vision-based strategy for pose estimation of aerial vehicles. The vast majority of approaches make use of features to estimate motion. Conversely, the strategy we propose is based on a MR (Multi- Resolution) implementation of an image registration technique (Inverse Compositional Image Alignment ICIA) using direct methods. An on-board camera in a downwards-looking configuration, and the assumption of planar scenes, are the bases of the algorithm. The motion between frames (rotation and translation) is recovered by decomposing the frame-to-frame homography obtained by the ICIA algorithm applied to a patch that covers around the 80% of the image. When the visual estimation is required (e.g. GPS drop-out), this motion is integrated with the previous known estimation of the vehicles’ state, obtained from the on-board sensors (GPS/IMU), and the subsequent estimations are based only on the vision-based motion estimations. The proposed strategy is tested with real flight data in representative stages of a flight: cruise, landing, and take-off, being two of those stages considered critical: take-off and landing. The performance of the pose estimation strategy is analyzed by comparing it with the GPS/IMU estimations. Results show correlation between the visual estimation obtained with the MR-ICIA and the GPS/IMU data, that demonstrate that the visual estimation can be used to provide a good approximation of the vehicle’s state when it is required (e.g. GPS drop-outs). In terms of performance, the proposed strategy is able to maintain an estimation of the vehicle’s state for more than one minute, at real-time frame rates based, only on visual information.

Reactive image-based collision avoidance system for unmanned aircraft systems

Approximately 20 years have passed now since the NTSB issued its original recommendation to expedite development, certification and production of low-cost proximity warning and conflict detection systems for general aviation [1]. While some systems are in place (TCAS [2]), ¡¨see-and-avoid¡¨ remains the primary means of separation between light aircrafts sharing the national airspace. The requirement for a collision avoidance or sense-and-avoid capability onboard unmanned aircraft has been identified by leading government, industry and regulatory bodies as one of the most significant challenges facing the routine operation of unmanned aerial systems (UAS) in the national airspace system (NAS) [3, 4]. In this thesis, we propose and develop a novel image-based collision avoidance system to detect and avoid an upcoming conflict scenario (with an intruder) without first estimating or filtering range. The proposed collision avoidance system (CAS) uses relative bearing ƒÛ and angular-area subtended ƒê , estimated from an image, to form a test statistic AS C . This test statistic is used in a thresholding technique to decide if a conflict scenario is imminent. If deemed necessary, the system will command the aircraft to perform a manoeuvre based on ƒÛ and constrained by the CAS sensor field-of-view. Through the use of a simulation environment where the UAS is mathematically modelled and a flight controller developed, we show that using Monte Carlo simulations a probability of a Mid Air Collision (MAC) MAC RR or a Near Mid Air Collision (NMAC) RiskRatio can be estimated. We also show the performance gain this system has over a simplified version (bearings-only ƒÛ ). This performance gain is demonstrated in the form of a standard operating characteristic curve. Finally, it is shown that the proposed CAS performs at a level comparable to current manned aviations equivalent level of safety (ELOS) expectations for Class E airspace. In some cases, the CAS may be oversensitive in manoeuvring the owncraft when not necessary, but this constitutes a more conservative and therefore safer, flying procedures in most instances.

The safety risk management of unmanned aircraft systems

The safety risk management process describes the systematic application of management policies, procedures and practices to the activities of communicating, consulting, establishing the context, and identifying, analysing, evaluating, treating, monitoring and reviewing risk. This process is undertaken to provide assurances that the risks of a particular unmanned aircraft system activity have been managed to an acceptable level. The safety risk management process and its outcomes form part of the documented safety case necessary to obtain approvals for unmanned aircraft system operations. It also guides the development of an organisation’s operations manual and is a primary component of an organisation’s safety management system. The aim of this chapter is to provide existing risk practitioners with a high level introduction to some of the unique issues and challenges in the application of the safety risk management process to unmanned aircraft systems. The scope is limited to safety risks associated with the operation of unmanned aircraft in the civil airspace system and over inhabited areas. The structure of the chapter is based on the safety risk management process as defined by the international risk management standard ISO 31000:2009 and draws on aviation safety resources provided by International Civil Aviation Organization, the Federal Aviation Administration and U.S. Department of Defense. References to relevant aviation safety regulations, programs of research and fielded systems are also provided.

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.

Airborne collision scenario flight tests : impact of angle measurement errors on reactive vision-based avoidance control

The future emergence of many types of airborne vehicles and unpiloted aircraft in the national airspace means collision avoidance is of primary concern in an uncooperative airspace environment. The ability to replicate a pilot’s see and avoid capability using cameras coupled with vision based avoidance control is an important part of an overall collision avoidance strategy. But unfortunately without range collision avoidance has no direct way to guarantee a level of safety. Collision scenario flight tests with two aircraft and a monocular camera threat detection and tracking system were used to study the accuracy of image-derived angle measurements. The effect of image-derived angle errors on reactive vision-based avoidance performance was then studied by simulation. The results show that whilst large angle measurement errors can significantly affect minimum ranging characteristics across a variety of initial conditions and closing speeds, the minimum range is always bounded and a collision never occurs.

HMM relative entropy rate concepts for vision-based aircraft manoeuvre detection

Machine vision is emerging as a viable sensing approach for mid-air collision avoidance (particularly for small to medium aircraft such as unmanned aerial vehicles). In this paper, using relative entropy rate concepts, we propose and investigate a new change detection approach that uses hidden Markov model filters to sequentially detect aircraft manoeuvres from morphologically processed image sequences. Experiments using simulated and airborne image sequences illustrate the performance of our proposed algorithm in comparison to other sequential change detection approaches applied to this application.

Perception Quality Evaluation with Visual and Infrared Cameras in Challenging Environmental Conditions

This work aims to contribute to the reliability and integrity of perceptual systems of unmanned ground vehicles (UGV). A method is proposed to evaluate the quality of sensor data prior to its use in a perception system by utilising a quality metric applied to heterogeneous sensor data such as visual and infrared camera images. The concept is illustrated specifically with sensor data that is evaluated prior to the use of the data in a standard SIFT feature extraction and matching technique. The method is then evaluated using various experimental data sets that were collected from a UGV in challenging environmental conditions, represented by the presence of airborne dust and smoke. In the first series of experiments, a motionless vehicle is observing a ’reference’ scene, then the method is extended to the case of a moving vehicle by compensating for its motion. This paper shows that it is possible to anticipate degradation of a perception algorithm by evaluating the input data prior to any actual execution of the algorithm.

Visual metrics for the evaluation of sensor data quality in outdoor perception

This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke. An example of application is given with monocular SLAM estimating the pose of the UGV while smoke is present in the environment. It is shown that the proposed novel quality metric can be used to anticipate situations where the quality of the pose estimate will be significantly degraded due to the input image data. This leads to decisions of advantageously switching between data sources (e.g. using infrared images instead of visual images).

Visual metrics for the evaluation of sensor data quality in outdoor perception

This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke.

Towards discrimination of challenging conditions for UGVs with visual and infrared sensors

This work aims to contribute to reliability and integrity in perceptual systems of autonomous ground vehicles. Information theoretic based metrics to evaluate the quality of sensor data are proposed and applied to visual and infrared camera images. The contribution of the proposed metrics to the discrimination of challenging conditions is discussed and illustrated with the presence of airborne dust and smoke.

Laser-camera data discrepancies and reliable perception in outdoor robotics

This work aims to promote integrity in autonomous perceptual systems, with a focus on outdoor unmanned ground vehicles equipped with a camera and a 2D laser range finder. A method to check for inconsistencies between the data provided by these two heterogeneous sensors is proposed and discussed. First, uncertainties in the estimated transformation between the laser and camera frames are evaluated and propagated up to the projection of the laser points onto the image. Then, for each pair of laser scan-camera image acquired, the information at corners of the laser scan is compared with the content of the image, resulting in a likelihood of correspondence. The result of this process is then used to validate segments of the laser scan that are found to be consistent with the image, while inconsistent segments are rejected. Experimental results illustrate how this technique can improve the reliability of perception in challenging environmental conditions, such as in the presence of airborne dust.

Port-Hamiltonian control of fully actuated underwater vehicles

This chapter presents a novel control strategy for trajectory tracking of underwater marine vehicles that are designed using port-Hamiltonian theory. A model for neutrally buoyant underwater vehicles is formulated as a PHS, and then the tracking controller is designed for the horizontal plane-surge, sway and yaw. The control design is done by formulating the error dynamics as a set-point regulation port-Hamiltonian control problem. The control design is formulated in two steps. In the first step, a static-feedback tracking controller is designed, and the second step integral action is added. The global asymptotic stability of the closed loop system is proved and the performance of the controller is illustrated using a model of an open-frame offshore underwater vehicle.

Energy-based motion control of marine vehicles using interconnection and damping assignment passivity-based control : a survey

This paper reviews some recent results in motion control of marine vehicles using a technique called Interconnection and Damping Assignment Passivity-based Control (IDA-PBC). This approach to motion control exploits the fact that vehicle dynamics can be described in terms of energy storage, distribution, and dissipation, and that the stable equilibrium points of mechanical systems are those at which the potential energy attains a minima. The control forces are used to transform the closed-loop dynamics into a port-controlled Hamiltonian system with dissipation. This is achieved by shaping the energy-storing characteristics of the system, modifying its interconnection structure (how the energy is distributed), and injecting damping. The end result is that the closed-loop system presents a stable equilibrium (hopefully global) at the desired operating point. By forcing the closed-loop dynamics into a Hamiltonian form, the resulting total energy function of the system serves as a Lyapunov function that can be used to demonstrate stability. We consider the tracking and regulation of fully actuated unmanned underwater vehicles, its extension to under-actuated slender vehicles, and also manifold regulation of under-actuated surface vessels. The paper is concluded with an outlook on future research.

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.