173 resultados para UAV Platform
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These lecture notes highlight some of the recent applications of multi-objective and multidisciplinary design optimisation in aeronautical design using the framework and methodology described in References 8, 23, 24 and in Part 1 and 2 of the notes. A summary of the methodology is described and the treatment of uncertainties in flight conditions parameters by the HAPEAs software and game strategies is introduced. Several test cases dealing with detailed design and computed with the software are presented and results discussed in section 4 of these notes.
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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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There is nothing new under the sun – so the saying goes, and in a digital age of recording oral histories, this holds true. Despite advances and innovations across the board in information and communication technology in the field of oral history it is essentially only the devices we record on that have changed. However, what has emerged is a plethora of ways that oral history interviews can be used to produce multimedia, or transmedia storytelling outputs- for exhibitions in public institutions, schools and by communities to engage interested groups, and in families and by individuals wanting to play with new ways of telling their family stories and histories. In 2010, QUT’s Creative Industries introduced a postgraduate unit called Transmedia Storytelling: From Interviewing to Multi-Platform, which was the first postgraduate course of its kind in Australia. Based in a Creative Writing discipline, but open to all coursework Masters, PhD, Research Masters and Doctorate of Creative Industries students, this unit introduces students to the theory and practice of semi-structured interviewing techniques, oral history conventions and applications, and the art of storytelling across various platforms.
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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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We have developed a new protein microarray (Immuno-Flow Protein Platform, IFPP) that utilizes a porous nitrocellulose (NC) membrane with printed spots of capture probes. The sample is pumped actively through the NC membrane, to enhance binding efficiency and introduce stringency. Compared to protein microarrays assayed with the conventional incubation-shaking method the rate of binding is enhanced on the IFPP by at least a factor of 10, so that the total assay time can be reduced drastically without compromising sensitivity. Similarly, the sensitivity can be improved. We demonstrate the detection of 1 pM of C-reactive protein (CRP) in 70 mu L of plasma within a total assay time of 7 min. The small sample and reagent volumes, combined with the speed of the assay, make our IFPP also well-suited for a point-of-care/near-patient setting. The potential clinical application of the IFPP is demonstrated by validating CRP detection both in human plasma and serum samples against standard clinical laboratory methods.
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PURPOSE: The prevalence of anaplastic lymphoma kinase (ALK) gene fusion (ALK positivity) in early-stage non-small-cell lung cancer (NSCLC) varies by population examined and detection method used. The Lungscape ALK project was designed to address the prevalence and prognostic impact of ALK positivity in resected lung adenocarcinoma in a primarily European population. METHODS: Analysis of ALK status was performed by immunohistochemistry (IHC) and fluorescent in situ hybridization (FISH) in tissue sections of 1,281 patients with adenocarcinoma in the European Thoracic Oncology Platform Lungscape iBiobank. Positive patients were matched with negative patients in a 1:2 ratio, both for IHC and for FISH testing. Testing was performed in 16 participating centers, using the same protocol after passing external quality assessment. RESULTS: Positive ALK IHC staining was present in 80 patients (prevalence of 6.2%; 95% CI, 4.9% to 7.6%). Of these, 28 patients were ALK FISH positive, corresponding to a lower bound for the prevalence of FISH positivity of 2.2%. FISH specificity was 100%, and FISH sensitivity was 35.0% (95% CI, 24.7% to 46.5%), with a sensitivity value of 81.3% (95% CI, 63.6% to 92.8%) for IHC 2+/3+ patients. The hazard of death for FISH-positive patients was lower than for IHC-negative patients (P = .022). Multivariable models, adjusted for patient, tumor, and treatment characteristics, and matched cohort analysis confirmed that ALK FISH positivity is a predictor for better overall survival (OS). CONCLUSION: In this large cohort of surgically resected lung adenocarcinomas, the prevalence of ALK positivity was 6.2% using IHC and at least 2.2% using FISH. A screening strategy based on IHC or H-score could be envisaged. ALK positivity (by either IHC or FISH) was related to better OS.
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This article describes the detection of DNA mutations using novel Au-Ag coated GaN substrate as SERS (surface-enhanced Raman spectroscopy) diagnostic platform. Oligonucleotide sequences corresponding to the BCR-ABL (breakpoint cluster region-Abelson) gene responsible for development of chronic myelogenous leukemia were used as a model system to demonstrate the discrimination between the wild type and Met244Val mutations. The thiolated ssDNA (single-strand DNA) was immobilized on the SERS-active surface and then hybridized to a labeled target sequence from solution. An intense SERS signal of the reporter molecule MGITC was detected from the complementary target due to formation of double helix. The SERS signal was either not observed, or decreased dramatically for a negative control sample consisting of labeled DNA that was not complementary to the DNA probe. The results indicate that our SERS substrate offers an opportunity for the development of novel diagnostic assays.
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Plants are an attractive alternative to conventional expression systems for the production of recombinant proteins and useful biologics, however, the economic viability of plant made proteins is strongly yield dependent. This study aimed to improve transgene expression levels in the plant host Nicotiana benthamiana using the Agroinfiltration transient expression platform. Independent investigation of the physical, chemical and genetic features associated with Agroinfiltration identified factors that improved transformation frequencies, elevated transgene expression levels and ultimately improved protein yield. The major outcome of this research was a novel hyper-expression system for biofarming recombinant proteins in plants.
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The UAV challenge takes place every year. Teams of compteitors compete to use an Unmanned Airborne Vehicle to locate a simulated lost person and deliver water.
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With the increase in complexity of engineering projects and design quality in the construction industry, the traditional two-dimensional "Information Island" approach to design is becoming less able to meet current design needs due to its lack of coordination and information sharing. Collaborative design using a Build Information Modeling (BIM) technology platform promises to provide an effective means of designing and communicating through networking and real-time data sharing. This paper first analyzes the shortcomings of the two-dimensional design process and the potential application of collaborative design. By combining the attributes of BIM, a preliminary BIM-based building design collaborative platform is developed to improve the design approach and support a more collaborative design process. A real-life case is presented to demonstrate the feasibility and validity of the platform and its use in practice. From this, it is shown that BIM has the potential to realize effective information sharing and reduce errors, thereby improving design quality. The BIM-based building design collaborative platform presented is expected to provide the support needed for the extensive application of BIM in collaborative design and promote a new attitude to project management.
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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.