953 resultados para Drone aircraft.
Resumo:
This project aims to develop a methodology for designing and conducting a systems engineering analysis to build and fly continuously, day and night, propelled uniquely by solar energy for one week with a 0.25Kg payload consuming 0.5 watt without fuel or pollution. An airplane able to fly autonomously for many days could find many applications. Including coastal or border surveillance, atmospherical and weather research and prediction, environmental, forestry, agricultural, and oceanic monitoring, imaging for the media and real-estate industries, etc. Additional advantages of solar airplanes are their low cost and the simplicity with which they can be launched. For example, in the case of potential forest fire risks during a warm and dry period, swarms of solar airplanes, easily launched with the hand, could efficiently monitor a large surface, reporting rapidly any fire starts. This would allow a fast intervention and thus reduce the cost of such disaster, in terms of human and material losses. At higher dimension, solar HALE platforms are expected to play a major role as communication relays and could replace advantageously satellites in a near future.
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Principal Topic: Project structures are often created by entrepreneurs and large corporate organizations to develop new products. Since new product development projects (NPDP) are more often situated within a larger organization, intrapreneurship or corporate entrepreneurship plays an important role in bringing these projects to fruition. Since NPDP often involves the development of a new product using immature technology, we describe development of an immature technology. The Joint Strike Fighter (JSF) F-35 aircraft is being developed by the U.S. Department of Defense and eight allied nations. In 2001 Lockheed Martin won a $19 billion contract to develop an affordable, stealthy and supersonic all-weather strike fighter designed to replace a wide range of aging fighter aircraft. In this research we define a complex project as one that demonstrates a number of sources of uncertainty to a degree, or level of severity, that makes it extremely difficult to predict project outcomes, to control or manage project (Remington & Zolin, Forthcoming). Project complexity has been conceptualized by Remington and Pollock (2007) in terms of four major sources of complexity; temporal, directional, structural and technological complexity (See Figure 1). Temporal complexity exists when projects experience significant environmental change outside the direct influence or control of the project. The Global Economic Crisis of 2008 - 2009 is a good example of the type of environmental change that can make a project complex as, for example in the JSF project, where project managers attempt to respond to changes in interest rates, international currency exchange rates and commodity prices etc. Directional complexity exists in a project where stakeholders' goals are unclear or undefined, where progress is hindered by unknown political agendas, or where stakeholders disagree or misunderstand project goals. In the JSF project all the services and all non countries have to agree to the specifications of the three variants of the aircraft; Conventional Take Off and Landing (CTOL), Short Take Off/Vertical Landing (STOVL) and the Carrier Variant (CV). Because the Navy requires a plane that can take off and land on an aircraft carrier, that required a special variant of the aircraft design, adding complexity to the project. Technical complexity occurs in a project using technology that is immature or where design characteristics are unknown or untried. Developing a plane that can take off on a very short runway and land vertically created may highly interdependent technological challenges to correctly locate, direct and balance the lift fans, modulate the airflow and provide equivalent amount of thrust from the downward vectored rear exhaust to lift the aircraft and at the same time control engine temperatures. These technological challenges make costing and scheduling equally challenging. Structural complexity in a project comes from the sheer numbers of elements such as the number of people, teams or organizations involved, ambiguity regarding the elements, and the massive degree of interconnectedness between them. While Lockheed Martin is the prime contractor, they are assisted in major aspects of the JSF development by Northrop Grumman, BAE Systems, Pratt & Whitney and GE/Rolls-Royce Fighter Engineer Team and innumerable subcontractors. In addition to identifying opportunities to achieve project goals, complex projects also need to identify and exploit opportunities to increase agility in response to changing stakeholder demands or to reduce project risks. Complexity Leadership Theory contends that in complex environments adaptive and enabling leadership are needed (Uhl-Bien, Marion and McKelvey, 2007). Adaptive leadership facilitates creativity, learning and adaptability, while enabling leadership handles the conflicts that inevitably arise between adaptive leadership and traditional administrative leadership (Uhl-Bien and Marion, 2007). Hence, adaptive leadership involves the recognition and opportunities to adapt, while and enabling leadership involves the exploitation of these opportunities. Our research questions revolve around the type or source of complexity and its relationship to opportunity recognition and exploitation. For example, is it only external environmental complexity that creates the need for the entrepreneurial behaviours, such as opportunity recognition and opportunity exploitation? Do the internal dimensions of project complexity, such as technological and structural complexity, also create the need for opportunity recognition and opportunity exploitation? The Kropp, Zolin and Lindsay model (2009) describes a relationship between entrepreneurial orientation (EO), opportunity recognition (OR), and opportunity exploitation (OX) in complex projects, with environmental and organizational contextual variables as moderators. We extend their model by defining the affects of external complexity and internal complexity on OR and OX. ---------- Methodology/Key Propositions: When the environment complex EO is more likely to result in OR because project members will be actively looking for solutions to problems created by environmental change. But in projects that are technologically or structurally complex project leaders and members may try to make the minimum changes possible to reduce the risk of creating new problems due to delays or schedule changes. In projects with environmental or technological complexity project leaders who encourage the innovativeness dimension of EO will increase OR in complex projects. But projects with technical or structural complexity innovativeness will not necessarily result in the recognition and exploitation of opportunities due to the over-riding importance of maintaining stability in the highly intricate and interconnected project structure. We propose that in projects with environmental complexity creating the need for change and innovation project leaders, who are willing to accept and manage risk, are more likely to identify opportunities to increase project effectiveness and efficiency. In contrast in projects with internal complexity a much higher willingness to accept risk will be necessary to trigger opportunity recognition. In structurally complex projects we predict it will be less likely to find a relationship between risk taking and OP. When the environment is complex, and a project has autonomy, they will be motivated to execute opportunities to improve the project's performance. In contrast, when the project has high internal complexity, they will be more cautious in execution. When a project experiences high competitive aggressiveness and their environment is complex, project leaders will be motivated to execute opportunities to improve the project's performance. In contrast, when the project has high internal complexity, they will be more cautious in execution. This paper reports the first stage of a three year study into the behaviours of managers, leaders and team members of complex projects. We conduct a qualitative study involving a Group Discussion with experienced project leaders. The objective is to determine how leaders of large and potentially complex projects perceive that external and internal complexity will influence the affects of EO on OR. ---------- Results and Implications: These results will help identify and distinguish the impact of external and internal complexity on entrepreneurial behaviours in NPDP. Project managers will be better able to quickly decide how and when to respond to changes in the environment and internal project events.
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New air traffic automated separation management concepts are constantly under investigation. Yet most of the automated separation management algorithms proposed over the last few decades have assumed either perfect communication or exact knowledge of all aircraft locations. In realistic environments, these idealized assumptions are not valid and any communication failure can potentially lead to disastrous outcomes. This paper examines the separation performance behavior of several popular algorithms during periods of information loss. This comparison is done through simulation studies. These simulation studies suggest that communication failure can cause the performance of these separation management algorithms to degrade significantly. This paper also describes some preliminary flight tests.
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Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of the sensors involved (as opposed to radar). This paper describes the development and evaluation of a vision-based collision detection algorithm suitable for fixed-wing aerial robotics. The system was evaluated using highly realistic vision data of the moments leading up to a collision. Based on the collected data, our detection approaches were able to detect targets at distances ranging from 400m to about 900m. These distances (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning of between 8-10 seconds ahead of impact, which approaches the 12.5 second response time recommended for human pilots. We make use of the enormous potential of graphic processing units to achieve processing rates of 30Hz (for images of size 1024-by- 768). Currently, integration in the final platform is under way.
Resumo:
In recent years, unmanned aerial vehicles (UAVs) have been widely used in combat, and their potential applications in civil and commercial roles are also receiving considerable attention by industry and the research community. There are numerous published reports of UAVs used in Earth science missions [1], fire-fighting [2], and border security [3] trials, with other speculative deployments, including applications in agriculture, communications, and traffic monitoring. However, none of these UAVs can demonstrate an equivalent level of safety to manned aircraft, particularly in the case of an engine failure, which would require an emergency or forced landing. This may be arguably the main factor that has prevented these UAV trials from becoming full-scale commercial operations, as well as restricted operations of civilian UAVs to only within segregated airspace.
Resumo:
Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of vision sensors (as opposed to radar and TCAS). This paper describes the development and evaluation of a real-time vision-based collision detection system suitable for fixed-wing aerial robotics. Using two fixed-wing UAVs to recreate various collision-course scenarios, we were able to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. This type of image data is extremely scarce and was invaluable in evaluating the detection performance of two candidate target detection approaches. Based on the collected data, our detection approaches were able to detect targets at distances ranging from 400m to about 900m. These distances (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning of between 8-10 seconds ahead of impact, which approaches the 12.5 second response time recommended for human pilots. We overcame the challenge of achieving real-time computational speeds by exploiting the parallel processing architectures of graphics processing units found on commercially-off-the-shelf graphics devices. Our chosen GPU device suitable for integration onto UAV platforms can be expected to handle real-time processing of 1024 by 768 pixel image frames at a rate of approximately 30Hz. Flight trials using manned Cessna aircraft where all processing is performed onboard will be conducted in the near future, followed by further experiments with fully autonomous UAV platforms.
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This paper details the design of an autonomous helicopter control system using a low cost sensor suite. Control is maintained using simple nested PID loops. Aircraft attitude, velocity, and height is estimated using an in-house designed IMU and vision system. Information is combined using complimentary filtering. The aircraft is shown to be stabilised and responding to high level demands on all axes, including heading, height, lateral velocity and longitudinal velocity.
Resumo:
This paper details the design of an autonomous helicopter control system using a low cost sensor suite. Control is maintained using simple nested PID loops. Aircraft attitude, velocity, and height is estimated using an in-house designed IMU and vision system. Information is combined using complimentary filtering. The aircraft is shown to be stabilised and responding to high level demands on all axes, including heading, height, lateral velocity and longitudinal velocity.
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This paper considers the pros and cons of using Behavioural cloning for the development of low-level helicopter automation modules. Over the course of this project several Behavioural cloning approaches have been investigated. The results of the most effective Behavioural cloning approach are then compared to PID modules designed for the same aircraft. The comparison takes into consideration development time, reliability, and control performance. It has been found that Behavioural cloning techniques employing local approximators and a wide state-space coverage during training can produce stabilising control modules in less time than tuning PID controllers. However, performance and reliabity deficits have been found to exist with the Behavioural Cloning, attributable largely to the time variant nature of the dynamics due to the operating environment, and the pilot actions being poor for teaching. The final conclusion drawn here is that tuning PID modules remains superior to behavioural cloning for low-level helicopter automation.
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This paper presents an Airborne Systems Laboratory for Automation Research. The Airborne Systems Laboratory (ASL) is a Cessna 172 aircraft that has been specially modified and equipped by ARCAA specifically for research in future aircraft automation technologies, including Unmanned Airborne Systems (UAS). This capability has been developed over a long period of time, initially through the hire of aircraft, and finally through the purchase and modification of a dedicated flight-testing capability. The ASL has been equipped with a payload system that includes the provision of secure mounting, power, aircraft state data, flight management system and real-time subsystem. Finally, this system has been deployed in a cost effective platform allowing real-world flight-testing on a range of projects.
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This paper presents the application of advanced optimization techniques to unmanned aerial system mission path planning system (MPPS) using multi-objective evolutionary algorithms (MOEAs). Two types of multi-objective optimizers are compared; the MOEA nondominated sorting genetic algorithm II and a hybrid-game strategy are implemented to produce a set of optimal collision-free trajectories in a three-dimensional environment. The resulting trajectories on a three-dimensional terrain are collision-free and are represented by using Bézier spline curves from start position to target and then target to start position or different positions with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of adding a hybrid-game strategy to a MOEA and for a MPPS.
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CFD has been successfully used in the optimisation of aerodynamic surfaces using a given set of parameters such as Mach numbers and angle of attack. While carrying out a multidisciplinary design optimisation one deals with situations where the parameters have some uncertain attached. Any optimisation carried out for fixed values of input parameters gives a design which may be totally unacceptable under off-design conditions. The challenge is to develop a robust design procedure which takes into account the fluctuations in the input parameters. In this work, we attempt this using a modified Taguchi approach. This is incorporated into an evolutionary algorithm with many features developed in house. The method is tested for an UCAV design which simultaneously handles aerodynamics, electromagnetics and maneuverability. Results demonstrate that the method has considerable potential.
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This paper discusses similarities and differences in autonomous helicopters developed at USC and CSIRO. The most significant differences are in the accuracy and sample rate of the sensor systems used for control. The USC vehicle, like a number of others, makes use of a sensor suite that costs an order of magnitude more than the vehicle. The CSIRO system, by contrast, utilizes low-cost inertial, magnetic, vision and GPS to achieve the same ends. We describe the architecture of both autonomous helicopters, discuss the design issues and present comparative results.
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In this paper we describe a low-cost flight control system for a small (60 class) helicopter which is part of a larger project to develop an autonomous flying vehicle. Our approach differs from that of others in not using an expensive inertial/GPS sensing system. The primary sensors for vehicle stabilization are a low-cost inertial sensor and a pair of CMOS cameras. We describe the architecture of our flight control system, the inertial and visual sensing subsystems and present some flight control results.