951 resultados para Bombing, Aerial


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The Australian Civil Aviation Safety Authority (CASA) currently lists more than 100 separate entities or organisations which maintain a UAS Operator Certificate (UOC) [1]. Approved operations are overwhelmingly a permutation of aerial photography, surveillance, survey or spotting and predominantly, are restricted to Visual Line of Sight (VLOS) operations, below 400 feet, and not within 3 NM of an aerodrome. However, demand is increasing for a Remote Piloted Aerial System (RPAS) regulatory regime which facilitates more expansive operations, in particular unsegregated, Beyond Visual Line of Sight (BVLOS) operations. Despite this demand, there is national and international apprehension regarding the necessary levels of airworthiness and operational regulation required to maintain safety and minimise the risk associated with unsegregated operations. Fundamental to addressing these legitimate concerns will be the mechanisms that underpin safe separation and collision avoidance. Whilst a large body of research has been dedicated to investigating on-board, Sense and Avoid (SAA) technology necessary to meet this challenge, this paper focuses on the contribution of the NAS to separation assurance, and how it will support, as well as complicate RPAS integration. The paper collates and presents key, but historically disparate, threads of Australian RPAS and NAS related information, and distils it with a filter focused on minimising RPAS collision risk. Our ongoing effort is motivated by the need to better understand the separation assurance contribution provided by the NAS layers, in the first instance, and subsequently employ this information to identify scenarios where the coincident collision risk is demonstrably low, providing legitimate substantiation for concessions on equipage and airworthiness standards.

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Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

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Salinity is a major threat to sustainable agriculture worldwide. Plant NHX exchangers play an important role in conferring salt tolerance under salinity stress. In this study, a vacuolar Na+/H+ antiporter gene VrNHX1 (Genbank Accession No. JN656211.1) from mungbean (Vigna radiata) was introduced into cowpea (Vigna unguiculata) by the Agrobacterium tumefaciens-mediated transformation method. Polymerase chain reaction and Southern blot hybridization confirmed the stable integration of VrNHX1 into the cowpea genome. Comparative expression analysis by semi-quantitative RT-PCR revealed higher expression of VrNHX1 in transgenic cowpea plants than wild-type. Under salt stress conditions, T2 transgenic 35S:VrNHX1 cowpea lines exhibited higher tolerance to 200 mM NaCl treatment than wild-type. Furthermore, T2 transgenic 35S:VrNHX1 lines maintained a higher K+/Na+ ratio in the aerial parts under salt stress and accumulated higher [Na+] in roots than wild-type. Physiological analysis revealed lower levels of lipid peroxidation, hydrogen peroxide and oxygen radical production but higher levels of relative water content and proline, ascorbate and chlorophyll contents in T2 transgenic 35S:VrNHX1 lines.

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Sparse optical flow algorithms, such as the Lucas-Kanade approach, provide more robustness to noise than dense optical flow algorithms and are the preferred approach in many scenarios. Sparse optical flow algorithms estimate the displacement for a selected number of pixels in the image. These pixels can be chosen randomly. However, pixels in regions with more variance between the neighbours will produce more reliable displacement estimates. The selected pixel locations should therefore be chosen wisely. In this study, the suitability of Harris corners, Shi-Tomasi's “Good features to track", SIFT and SURF interest point extractors, Canny edges, and random pixel selection for the purpose of frame-by-frame tracking using a pyramidical Lucas-Kanade algorithm is investigated. The evaluation considers the important factors of processing time, feature count, and feature trackability in indoor and outdoor scenarios using ground vehicles and unmanned aerial vehicles, and for the purpose of visual odometry estimation.

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This special issue of the Journal of Field Robotics focuses on low altitude flight of UAVs with a particular emphasis on fully implemented systems that were tested in relevant environments or deployed in regular operations.

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This chapter describes decentralized data fusion algorithms for a team of multiple autonomous platforms. Decentralized data fusion (DDF) provides a useful basis with which to build upon for cooperative information gathering tasks for robotic teams operating in outdoor environments. Through the DDF algorithms, each platform can maintain a consistent global solution from which decisions may then be made. Comparisons will be made between the implementation of DDF using two probabilistic representations. The first, Gaussian estimates and the second Gaussian mixtures are compared using a common data set. The overall system design is detailed, providing insight into the overall complexity of implementing a robust DDF system for use in information gathering tasks in outdoor UAV applications.

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This thesis presents an approach for a vertical infrastructure inspection using a vertical take-off and landing (VTOL) unmanned aerial vehicle and shared autonomy. Inspecting vertical structure such as light and power distribution poles is a difficult task. There are challenges involved with developing such an inspection system, such as flying in close proximity to a target while maintaining a fixed stand-off distance from it. The contributions of this thesis fall into three main areas. Firstly, an approach to vehicle dynamic modeling is evaluated in simulation and experiments. Secondly, EKF-based state estimators are demonstrated, as well as estimator-free approaches such as image based visual servoing (IBVS) validated with motion capture ground truth data. Thirdly, an integrated pole inspection system comprising a VTOL platform with human-in-the-loop control, (shared autonomy) is demonstrated. These contributions are comprehensively explained through a series of published papers.

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This paper proposes new techniques for aircraft shape estimation, passive ranging, and shape-adaptive hidden Markov model filtering which are suitable for a monocular vision-based non-cooperative collision avoidance system. Vision-based passive ranging is an important missing technology that could play a significant role in resolving the sense-and-avoid problem in un-manned aerial vehicles (UAVs); a barrier hindering the wider adoption of UAVs for civilian applications. The feasibility of the pro- posed shape estimation, passive ranging and shape-adaptive filtering techniques is evaluated on flight test data.

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We present an approach for the inspection of vertical pole-like infrastructure using a vertical take-off and landing (VTOL) unmanned aerial vehicle and shared autonomy. Inspecting vertical structures, such as light and power distribution poles, is a time consuming, dangerous and expensive task with high operator workload. To address these issues, we propose a VTOL platform that can operate at close-quarters, whilst maintaining a safe stand-off distance and rejecting environmental disturbances. We adopt an Image based Visual Servoing (IBVS) technique using only two line features to stabilise the vehicle with respect to a pole. Visual, inertial and sonar data are used, making the approach suitable for indoor or GPS-denied environments. Results from simulation and outdoor flight experiments demonstrate the system is able to successfully inspect and circumnavigate a pole.

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Mobile robots and animals alike must effectively navigate their environments in order to achieve their goals. For animals goal-directed navigation facilitates finding food, seeking shelter or migration; similarly robots perform goal-directed navigation to find a charging station, get out of the rain or guide a person to a destination. This similarity in tasks extends to the environment as well; increasingly, mobile robots are operating in the same underwater, ground and aerial environments that animals do. Yet despite these similarities, goal-directed navigation research in robotics and biology has proceeded largely in parallel, linked only by a small amount of interdisciplinary research spanning both areas. Most state-of-the-art robotic navigation systems employ a range of sensors, world representations and navigation algorithms that seem far removed from what we know of how animals navigate; their navigation systems are shaped by key principles of navigation in ‘real-world’ environments including dealing with uncertainty in sensing, landmark observation and world modelling. By contrast, biomimetic animal navigation models produce plausible animal navigation behaviour in a range of laboratory experimental navigation paradigms, typically without addressing many of these robotic navigation principles. In this paper, we attempt to link robotics and biology by reviewing the current state of the art in conventional and biomimetic goal-directed navigation models, focusing on the key principles of goal-oriented robotic navigation and the extent to which these principles have been adapted by biomimetic navigation models and why.

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Acid sulfate soils (ASS) is a stress factor that is responsible for the failure of some mangrove restoration projects, including abandoned aquaculture ponds converted from mangrove ecosystems. Through experimental and field studies, this research provides a better understanding of the biogeochemistry of ASS disturbance and the response of mangrove seedlings (Rhizophoraceae) under high metal levels and acidic conditions. This study found that mangrove restorations under ASS disturbance can work but with lower numbers of survived seedlings. To prevent toxicity under high levels of metal, seedlings retained metals in their roots and sparingly distributed them into aerial parts with low mobility. The presence of high levels of potential acidity parameters would allow pyrite to oxidise, thus increasing metal levels and acidity, which in turn affected the survival and growth of the seedlings.

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This paper deals with constrained image-based visual servoing of circular and conical spiral motion about an unknown object approximating a single image point feature. Effective visual control of such trajectories has many applications for small unmanned aerial vehicles, including surveillance and inspection, forced landing (homing), and collision avoidance. A spherical camera model is used to derive a novel visual-predictive controller (VPC) using stability-based design methods for general nonlinear model-predictive control. In particular, a quasi-infinite horizon visual-predictive control scheme is derived. A terminal region, which is used as a constraint in the controller structure, can be used to guide appropriate reference image features for spiral tracking with respect to nominal stability and feasibility. Robustness properties are also discussed with respect to parameter uncertainty and additive noise. A comparison with competing visual-predictive control schemes is made, and some experimental results using a small quad rotor platform are given.

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This paper details the initial design and planning of a Field Programmable Gate Array (FPGA) implemented control system that will enable a path planner to interact with a MAVLink based flight computer. The design is aimed at small Unmanned Aircraft Vehicles (UAV) under autonomous operation which are typically subject to constraints arising from limited on-board processing capabilities, power and size. An FPGA implementation for the de- sign is chosen for its potential to address such limitations through low power and high speed in-hardware computation. The MAVLink protocol offers a low bandwidth interface for the FPGA implemented path planner to communicate with an on-board flight computer. A control system plan is presented that is capable of accepting a string of GPS waypoints generated on-board from a previously developed in- hardware Genetic Algorithm (GA) path planner and feeding them to the open source PX4 autopilot, while simultaneously respond- ing with flight status information.

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Echolocation calls of 119 bats belonging to 12 species in three families from Antillean islands of Puerto Rico, Dominica, and St. Vincent were recorded by using time-expansion methods. Spectrograms of calls and descriptive statistics of five temporal and frequency variables measured from calls are presented. The echolocation calls of many of these species, particularly those in the family Phyllostomidae, have not been described previously. The wing morphology of each taxon is described and related to the structure of its echolocation calls and its foraging ecology. Of slow aerial-hawking insectivores, the Mormoopidae and Natalidae Mormoops blainvillii, Pteronotus davyi davyi, P. quadridens fuliginosus, and Natalus stramineus stramineus can forage with great manoeuvrability in background-cluttered space (close to vegetation), and are able to hover. Pteronotus parnellii portoricensis is able to fly and echolocate in highly-cluttered space (dense vegetation). Among frugivores, nectarivores and omnivores in the family Phyllostomidae, Brachyphylla cavernarum intermedia is adapted to foraging in the edges of vegetation in background-cluttered space, while Erophylla bombifrons bombifrons, Glossophaga longirostris rostrata, Artibeus jamaicensis jamaicensis, A. jamaicensis schwartzi and Stenoderma rufum darioi are adapted to foraging under canopies in highly-cluttered space and do not have speed or efficiency in commuting flight. In contrast, Monophyllus plethodon luciae, Sturnira lilium angeli and S. lilium paulsoni are adapted to fly in highly-cluttered space, but can also fly fast and efficiently in open areas.