Multi-objective mission flight planning in civil unmanned aerial systems

Unmanned Aerial Vehicles (UAVs) are emerging as an ideal platform for a wide range of civil applications such as disaster monitoring, atmospheric observation and outback delivery. However, the operation of UAVs is currently restricted to specially segregated regions of airspace outside of the National Airspace System (NAS). Mission Flight Planning (MFP) is an integral part of UAV operation that addresses some of the requirements (such as safety and the rules of the air) of integrating UAVs in the NAS. Automated MFP is a key enabler for a number of UAV operating scenarios as it aids in increasing the level of onboard autonomy. For example, onboard MFP is required to ensure continued conformance with the NAS integration requirements when there is an outage in the communications link. MFP is a motion planning task concerned with finding a path between a designated start waypoint and goal waypoint. This path is described with a sequence of 4 Dimensional (4D) waypoints (three spatial and one time dimension) or equivalently with a sequence of trajectory segments (or tracks). It is necessary to consider the time dimension as the UAV operates in a dynamic environment. Existing methods for generic motion planning, UAV motion planning and general vehicle motion planning cannot adequately address the requirements of MFP. The flight plan needs to optimise for multiple decision objectives including mission safety objectives, the rules of the air and mission efficiency objectives. Online (in-flight) replanning capability is needed as the UAV operates in a large, dynamic and uncertain outdoor environment. This thesis derives a multi-objective 4D search algorithm entitled Multi- Step A* (MSA*) based on the seminal A* search algorithm. MSA* is proven to find the optimal (least cost) path given a variable successor operator (which enables arbitrary track angle and track velocity resolution). Furthermore, it is shown to be of comparable complexity to multi-objective, vector neighbourhood based A* (Vector A*, an extension of A*). A variable successor operator enables the imposition of a multi-resolution lattice structure on the search space (which results in fewer search nodes). Unlike cell decomposition based methods, soundness is guaranteed with multi-resolution MSA*. MSA* is demonstrated through Monte Carlo simulations to be computationally efficient. It is shown that multi-resolution, lattice based MSA* finds paths of equivalent cost (less than 0.5% difference) to Vector A* (the benchmark) in a third of the computation time (on average). This is the first contribution of the research. The second contribution is the discovery of the additive consistency property for planning with multiple decision objectives. Additive consistency ensures that the planner is not biased (which results in a suboptimal path) by ensuring that the cost of traversing a track using one step equals that of traversing the same track using multiple steps. MSA* mitigates uncertainty through online replanning, Multi-Criteria Decision Making (MCDM) and tolerance. Each trajectory segment is modeled with a cell sequence that completely encloses the trajectory segment. The tolerance, measured as the minimum distance between the track and cell boundaries, is the third major contribution. Even though MSA* is demonstrated for UAV MFP, it is extensible to other 4D vehicle motion planning applications. Finally, the research proposes a self-scheduling replanning architecture for MFP. This architecture replicates the decision strategies of human experts to meet the time constraints of online replanning. Based on a feedback loop, the proposed architecture switches between fast, near-optimal planning and optimal planning to minimise the need for hold manoeuvres. The derived MFP framework is original and shown, through extensive verification and validation, to satisfy the requirements of UAV MFP. As MFP is an enabling factor for operation of UAVs in the NAS, the presented work is both original and significant.

Robust real time multi-layer foreground segmentation

Many surveillance applications (object tracking, abandoned object detection) rely on detecting changes in a scene. Foreground segmentation is an effective way to extract the foreground from the scene, but these techniques cannot discriminate between objects that have temporarily stopped and those that are moving. We propose a series of modifications to an existing foreground segmentation system\cite{Butler2003} so that the foreground is further segmented into two or more layers. This yields an active layer of objects currently in motion and a passive layer of objects that have temporarily ceased motion which can itself be decomposed into multiple static layers. We also propose a variable threshold to cope with variable illumination, a feedback mechanism that allows an external process (i.e. surveillance system) to alter the motion detectors state, and a lighting compensation process and a shadow detector to reduce errors caused by lighting inconsistencies. The technique is demonstrated using outdoor surveillance footage, and is shown to be able to effectively deal with real world lighting conditions and overlapping objects.

Abandoned object detection using multi-layer motion detection

Abandoned object detection (AOD) systems are required to run in high traffic situations, with high levels of occlusion. Systems rely on background segmentation techniques to locate abandoned objects, by detecting areas of motion that have stopped. This is often achieved by using a medium term motion detection routine to detect long term changes in the background. When AOD systems are integrated into person tracking system, this often results in two separate motion detectors being used to handle the different requirements. We propose a motion detection system that is capable of detecting medium term motion as well as regular motion. Multiple layers of medium term (static) motion can be detected and segmented. We demonstrate the performance of this motion detection system and as part of an abandoned object detection system.

Multi-sensor tracking using a scalable condensation filter

Surveillance and tracking systems typically use a single colour modality for their input. These systems work well in controlled conditions but often fail with low lighting, shadowing, smoke, dust, unstable backgrounds or when the foreground object is of similar colouring to the background. With advances in technology and manufacturing techniques, sensors that allow us to see into the thermal infrared spectrum are becoming more affordable. By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using visible light only for surveillance and tracking. Thermal images are not affected by lighting or shadowing and are not overtly affected by smoke, dust or unstable backgrounds. We propose and evaluate three approaches for fusing visual and thermal images for person tracking. We also propose a modified condensation filter to track and aid in the fusion of the modalities. We compare the proposed fusion schemes with using the visual and thermal domains on their own, and demonstrate that significant improvements can be achieved by using multiple modalities.

Multi-spectral fusion for surveillance systems

Surveillance systems such as object tracking and abandoned object detection systems typically rely on a single modality of colour video for their input. These systems work well in controlled conditions but often fail when low lighting, shadowing, smoke, dust or unstable backgrounds are present, or when the objects of interest are a similar colour to the background. Thermal images are not affected by lighting changes or shadowing, and are not overtly affected by smoke, dust or unstable backgrounds. However, thermal images lack colour information which makes distinguishing between different people or objects of interest within the same scene difficult. ----- By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using either modality individually. We evaluate four approaches for fusing visual and thermal images for use in a person tracking system (two early fusion methods, one mid fusion and one late fusion method), in order to determine the most appropriate method for fusing multiple modalities. We also evaluate two of these approaches for use in abandoned object detection, and propose an abandoned object detection routine that utilises multiple modalities. To aid in the tracking and fusion of the modalities we propose a modified condensation filter that can dynamically change the particle count and features used according to the needs of the system. ----- We compare tracking and abandoned object detection performance for the proposed fusion schemes and the visual and thermal domains on their own. Testing is conducted using the OTCBVS database to evaluate object tracking, and data captured in-house to evaluate the abandoned object detection. Our results show that significant improvement can be achieved, and that a middle fusion scheme is most effective.

Load–frequency control : a GA-based multi-agent reinforcement learning

The load–frequency control (LFC) problem has been one of the major subjects in a power system. In practice, LFC systems use proportional–integral (PI) controllers. However since these controllers are designed using a linear model, the non-linearities of the system are not accounted for and they are incapable of gaining good dynamical performance for a wide range of operating conditions in a multi-area power system. A strategy for solving this problem because of the distributed nature of a multi-area power system is presented by using a multi-agent reinforcement learning (MARL) approach. It consists of two agents in each power area; the estimator agent provides the area control error (ACE) signal based on the frequency bias estimation and the controller agent uses reinforcement learning to control the power system in which genetic algorithm optimisation is used to tune its parameters. This method does not depend on any knowledge of the system and it admits considerable flexibility in defining the control objective. Also, by finding the ACE signal based on the frequency bias estimation the LFC performance is improved and by using the MARL parallel, computation is realised, leading to a high degree of scalability. Here, to illustrate the accuracy of the proposed approach, a three-area power system example is given with two scenarios.

A new family of multi-output DC-DC converter topologies to supply an asymmetrical four-level diode-clamped inverter

Purpose Multi-level diode-clamped inverters have the challenge of capacitor voltage balancing when the number of DC-link capacitors is three or more. On the other hand, asymmetrical DC-link voltage sources have been applied to increase the number of voltage levels without increasing the number of switches. The purpose of this paper is to show that an appropriate multi-output DC-DC converter can resolve the problem of capacitor voltage balancing and utilize the asymmetrical DC-link voltages advantages. Design/methodology/approach A family of multi-output DC-DC converters is presented in this paper. The application of these converters is to convert the output voltage of a photovoltaic (PV) panel to regulate DC-link voltages of an asymmetrical four-level diode-clamped inverter utilized for domestic applications. To verify the versatility of the presented topology, simulations have been directed for different situations and results are presented. Some related experiments have been developed to examine the capabilities of the proposed converters. Findings The three-output voltage-sharing converters presented in this paper have been mathematically analysed and proven to be appropriate to improve the quality of the residential application of PV by means of four-level asymmetrical diode-clamped inverter supplying highly resistive loads. Originality/value This paper shows that an appropriate multi-output DC-DC converter can resolve the problem of capacitor voltage balancing and utilize the asymmetrical DC-link voltages advantages and that there is a possibility of operation at high-modulation index despite reference voltage magnitude and power factor variations.

Multi-output buck-boost converter with enhanced dynamic response to load and input voltage changes

This paper presents a new multi-output DC/DC converter topology that has step-up and step-down conversion capabilities. In this topology, several output voltages can be generated which can be used in different applications such as multilevel converters with diode-clamped topology or power supplies with several voltage levels. Steady state and dynamic equations of the proposed multi-output converter have been developed, that can be used for steady state and transient analysis. Two control techniques have been proposed for this topology based on constant and dynamic hysteresis band height control to address different applications. Simulations have been performed for different operating modes and load conditions to verify the proposed topology and its control technique. Additionally, a laboratory prototype is designed and implemented to verify the simulation results.

Raman spectroscopic study of the multi-anion mineral dixenite CuMn2+14Fe3+(AsO3)5(SiO4)2(AsO4)(OH)6

The mixed anion mineral dixenite has been studied by Raman spectroscopy, complimented with infrared spectroscopy. The Raman spectrum of dixenite shows bands at 839 and 813 cm-1 assigned to the (AsO3)3- symmetric and antisymmetric stretching modes. The most intense Raman band of dixenite is the band at 526 cm-1 and is assigned to the ν2 AsO33- bending mode. DFT calculations enabled the position of AsO22- symmetric stretching mode at 839 cm-1, the antisymmetric stretching mode at 813 cm-1, and the deformation mode at 449 cm-1 to be calculated. Raman bands at 1026 and 1057 cm-1 are assigned to the SiO42- symmetric stretching vibrations and at 1349 and 1386 cm-1 to the SiO42- antisymmetric stretching vibrations. Both Raman and infrared spectra indicate the presence of water in the structure of dixenite. This brings into question the commonly accepted formula of dixenite as CuMn2+14Fe3+(AsO3)5(SiO4)2(AsO4)(OH)6. The formula may be better written as CuMn2+14Fe3+(AsO3)5(SiO4)2(AsO4)(OH)6•xH2O.

E-commerce experiences in the real estate industry : a preliminary study in regional Queensland

Computer systems have become commonplace in most SMEs and technology is increasingly becoming a part of doing business. In recent years, the Internet has become readily available to businesses; consequently there has been growing pressure on SMEs to take up e-commerce. However, e-commerce is perceived by many as being unproven in terms of business benefit. This research aims to determine what, if any, benefits are derived from assimilating e-commerce technologies into SME business processes. This paper presents three in-depth case studies from the Real Estate industry in a regional setting. Overall, findings were positive and identified the following experiences: enhanced business efficiencies, cost benefits, improved customer interactions and increased business return on investment.

Towards compatible and integrated airport and regional land use planning in Australia

Over the past decade privatised capital city airports in Australia have planned developed a range of non aviation commercial and retail land uses on airport land. Many surrounding municipalities consider this development in conflict with existing regional land use planning. Conversely airport operators are alarmed at continued urban consolidation and encroachment of incompatible regional development. Land use planning within and surrounding Australian capital city airports does not support compatible and integrated land use. It is currently a fragmented process due to: 1) current legislative and policy frameworks; 2) competing stakeholder priorities and interests; and 3) inadequate coordination and disjointed decision-making. This paper will examine privatised Australian airport development and consider three case studies to detail the context of airport and regional land use planning. A series of stakeholder workshops have served to inform the procedural dynamics and relationships between airport and regional decision-making. This exploratory research will assist in informing the knowledge gaps between aviation, airport development and broader urban land use policy. This paper will provide recommendations to enhance approaches to land use planning for airports and adjacent metropolitan regions in Australia and overseas.

Crime in Rural and Regional Areas

This Chapter provides an overview of available corrent data measuring crime in Australia's States and Territories broken down into regions and localities The data is limited, has reliability problems and lots of gaps. Nevertheless when the data are analysed according to offence type (in particulary violence versus property offences) an interesting but complicated empirical picture emerges that departs from what most scholars and policy makes have commonly assumed about crime and rural communities - that there is not much of it! The chapter begins with an assessment of the uses and limitations of different ways of measuring crime for those interested in a spatialised analysis of crome dispersion in rural communities.

Achieving cooperation in a distributed multi-robot team

DMAPS (Distributed Multi-Agent Planning System) is a planning system developed for distributed multi-robot teams based on MAPS (Multi-Agent Planning System). MAPS assumes that each agent has the same global view of the environment in order to determine the most suitable actions. This assumption fails when perception is local to the agents: each agent has only a partial and unique view of the environment. DMAPS addresses this problem by creating a probabilistic global view on each agent by fusing the perceptual information from each robot. The experimental results on consuming tasks show that while the probabilistic global view is not identical on each robot, the shared view is still effective in increasing performance of the team.