1000 resultados para Vehicle trajectories.


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In this paper, we concern ourselves with finding a control strategy that minimizes energy consumption along a trajectory connecting two given configurations. We develop an algorithm, based on our previous work with the time optimal problem, which provides implementable control strategies that are energy efficient. We find an interesting correlation between the duration of these trajectories and the optimal duration. We present the algorithm, control strategy and experimental results from our test-bed vehicle.

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Autonomous underwater vehicles (AUVs) are increasingly used, both in military and civilian applications. These vehicles are limited mainly by the intelligence we give them and the life of their batteries. Research is active to extend vehicle autonomy in both aspects. Our intent is to give the vehicle the ability to adapt its behavior under different mission scenarios (emergency maneuvers versus long duration monitoring). This involves a search for optimal trajectories minimizing time, energy or a combination of both. Despite some success stories in AUV control, optimal control is still a very underdeveloped area. Adaptive control research has contributed to cost minimization problems, but vehicle design has been the driving force for advancement in optimal control research. We look to advance the development of optimal control theory by expanding the motions along which AUVs travel. Traditionally, AUVs have taken the role of performing the long data gathering mission in the open ocean with little to no interaction with their surroundings, MacIver et al. (2004). The AUV is used to find the shipwreck, and the remotely operated vehicle (ROV) handles the exploration up close. AUV mission profiles of this sort are best suited through the use of a torpedo shaped AUV, Bertram and Alvarez (2006), since straight lines and minimal (0 deg - 30 deg) angular displacements are all that are necessary to perform the transects and grid lines for these applications. However, the torpedo shape AUV lacks the ability to perform low-speed maneuvers in cluttered environments, such as autonomous exploration close to the seabed and around obstacles, MacIver et al. (2004). Thus, we consider an agile vehicle capable of movement in six degrees of freedom without any preference of direction.

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This paper is concerned with the design and implementation of control strategies onto a test-bed vehicle with six degrees-of-freedom. We design our trajectories to be efficient in time and in power consumption. Moreover, we also consider cases when actuator failure can arise and discuss alternate control strategies in this situation. Our calculations are supplemented by experimental results.

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In this paper we consider the implementation of time and energy efficient trajectories onto a test-bed autonomous underwater vehicle. The trajectories are losely connected to the results of the application of the maximum principle to the controlled mechanical system. We use a numerical algorithm to compute efficient trajectories designed using geometric control theory to optimize a given cost function. Experimental results are shown for the time minimization problem.

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In this paper, we are concerned with the practical implementation of time optimal numerical techniques on underwater vehicles. We briefly introduce the model of underwater vehicle we consider and present the parameters for the test bed ODIN (Omni-Directional Intelligent Navigator). Then we explain the numerical method used to obtain time optimal trajectories with a structure suitable for the implementation. We follow this with a discussion on the modifications to be made considering the characteristics of ODIN. Finally, we illustrate our computations with some experimental results.

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Loop detectors are widely used on the motorway networks where they provide point speed and traffic volumes. Models have been proposed for temporal and spatial generalization of speed for average travel time estimation. Advancement in technology provides complementary data sources such as Bluetooth MAC Scanner (BMS), detecting the MAC ID of the Bluetooth devices transported by the traveller. Matching the data from two BMS stations provides individual vehicle travel time. Generally, on the motorways loops are closely spaced, whereas BMS are placed few kilometres apart. In this research, we fuse BMSs and loops data to define the trajectories of the Bluetooth vehicles. The trajectories are utilised to estimate the travel time statistics between any two points along the motorway. The proposed model is tested using simulation and validated with real data from Pacific motorway, Brisbane. Comparing the model with the linear interpolation based trajectory provides significant improvements.

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We have developed a Hierarchical Look-Ahead Trajectory Model (HiLAM) that incorporates the firing pattern of medial entorhinal grid cells in a planning circuit that includes interactions with hippocampus and prefrontal cortex. We show the model’s flexibility in representing large real world environments using odometry information obtained from challenging video sequences. We acquire the visual data from a camera mounted on a small tele-operated vehicle. The camera has a panoramic field of view with its focal point approximately 5 cm above the ground level, similar to what would be expected from a rat’s point of view. Using established algorithms for calculating perceptual speed from the apparent rate of visual change over time, we generate raw dead reckoning information which loses spatial fidelity over time due to error accumulation. We rectify the loss of fidelity by exploiting the loop-closure detection ability of a biologically inspired, robot navigation model termed RatSLAM. The rectified motion information serves as a velocity input to the HiLAM to encode the environment in the form of grid cell and place cell maps. Finally, we show goal directed path planning results of HiLAM in two different environments, an indoor square maze used in rodent experiments and an outdoor arena more than two orders of magnitude larger than the indoor maze. Together these results bridge for the first time the gap between higher fidelity bio-inspired navigation models (HiLAM) and more abstracted but highly functional bio-inspired robotic mapping systems (RatSLAM), and move from simulated environments into real-world studies in rodent-sized arenas and beyond.

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In this paper a nonlinear optimal controller has been designed for aerodynamic control during the reentry phase of the Reusable Launch Vehicle (RLV). The controller has been designed based on a recently developed technique Optimal Dynamic Inversion (ODI). For full state feedback the controller has required full information about the system states. In this work an Extended Kalman filter (EKF) is developed to estimate the states. The vehicle (RLV) has been has been consider as a nonlinear Six-Degree-Of-Freedom (6-DOF) model. The simulation results shows that EKF gives a very good estimation of the states and it is working well with ODI. The resultant trajectories are very similar to those obtained by perfect state feedback using ODI only.

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This paper addresses trajectory generation problem of a fixed-wing miniature air vehicle, constrained by bounded turn rate, to follow a given sequence of waypoints. An extremal path, named as g-trajectory, that transitions between two consecutive waypoint segments (obtained by joining two waypoints in sequence) in a time-optimal fashion is obtained. This algorithm is also used to track the maximum portion of waypoint segments with the desired shortest distance between the trajectory and the associated waypoint. Subsequently, the proposed trajectory is compared with the existing transition trajectory in the literature to show better performance in several aspects. Another optimal path, named as loop trajectory, is developed for the purpose of tracking the waypoints as well as the entire waypoint segments. This paper also proposes algorithms to generate trajectories in the presence of steady wind to meet the same objective as that of no-wind case. Due to low computational burden and simplicity in the design procedure, these trajectory generation approaches are implementable in real time for miniature air vehicles.

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4 p.

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Atmospheric particulate matter (PM) is genotoxic and recently was classified as carcinogenic to humans by the International Agency for Research on Cancer. PM chemical composition varies depending on source and atmospheric conditions. The Salmonella/microsome assay is the most used mutagenicity test and can identify the major chemical classes responsible for observed mutagenicity. The objective of this work was to characterize the mutagenicity of PM samples from a countryside city, Limeira, Brazil, which is influenced by heavy traffic and sugar cane biomass burning. Six samples of total PM were collected. Air mass backward trajectories were calculated. Organic extracts were assayed using the Salmonella/microsome microsuspension mutagenicity assay using TA98, YG1041, and TA1538, with and without metabolic activation (S9). YG1041 was the most sensitive strain and mutagenicity reached 9,700 revertants per m(3) without metabolic activation. Potency for TA1538 was higher than TA98, indicating that this strain should be considered in air mutagenicity studies. The increased response to YG1041 relative to TA98, and the decreased response with S9, suggests that nitroaromatics are the major contributors. Limeira is among the most mutagenic cities in the world. High mutagenicity in Limeira seems to occur when the air mass from the area of sugarcane production is mixed with air from the region impacted by anthropogenic activities such as traffic. An increase in the formation of nitro-polycyclic aromatic hydrocarbons may result from longer contact time between the aromatic compounds and the atmosphere with high NOx and ozone concentration, although more studies are required to confirm this hypothesis. Environ. Mol. Mutagen., 2015. © 2015 Wiley Periodicals, Inc.

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This thesis aims to fill the gap in the literature by examining the relationship between technological trajectories and environmental policy in the automotive industry, focusing on the role of environmental policies in unlocking the industry from fossil fuel path-dependence. It first explores the inducement mechanism that underpins the interaction between environmental policy and green technological advances, investigating under what conditions the European environmental transport policy portfolio and the intrinsic characteristics of assignees' knowledge boost worldwide green patent production. Subsequently, the thesis empirically analyses the dynamics of technological knowledge involved in technological trajectories assessing evolution patterns such as variation, selection and retention, in order to study the impact of policy implementation on technological knowledge related to electric and hybrid vehicle technologies. Finally, the thesis sheds light on the drivers that encourage a shift from incumbent internal combustion engine technologies towards low-emission vehicle technologies. This analysis tests whether tax-inclusive fuel prices and technological proximity between technological fields induce a shift from non-environmental inventions to environmentally friendly inventive activities and if they impact the competition between alternative vehicle technologies. The findings provide insights into the effectiveness of environmental policy in triggering inventive activities related to the development of alternative vehicle technologies. In addition, there is evidence that environmental policy redirects technological efforts towards a sustainable path and impacts the competition between low-emission vehicles.

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Intercontinental Ballistic Missiles are capable of placing a nuclear warhead at more than 5,000 km away from its launching base. With the lethal power of a nuclear warhead a whole city could be wiped out by a single weapon causing millions of deaths. This means that the threat posed to any country from a single ICBM captured by a terrorist group or launched by a 'rogue' state is huge. This threat is increasing as more countries are achieving nuclear and advanced launcher capabilities. In order to suppress or at least reduce this threat the United States created the National Missile Defense System which involved, among other systems, the development of long-range interceptors whose aim is to destroy incoming ballistic missiles in their midcourse phase. The Ballistic Missile Defense is a high-profile topic that has been the focus of political controversy lately when the U.S. decided to expand the Ballistic Missile system to Europe, with the opposition of Russia. However the technical characteristics of this system are mostly unknown by the general public. The Interception of an ICBM using a long range Interceptor Missile as intended within the Ground-Based Missile Defense System by the American National Missile Defense (NMD) implies a series of problems of incredible complexity: - The incoming missile has to be detected almost immediately after launch. - The incoming missile has to be tracked along its trajectory with a great accuracy. - The Interceptor Missile has to implement a fast and accurate guidance algorithm in order to reach the incoming missile as soon as possible. - The Kinetic Kill Vehicle deployed by the interceptor boost vehicle has to be able to detect the reentry vehicle once it has been deployed by ICBM, when it offers a very low infrared signature, in order to perform a final rendezvous manoeuvre. - The Kinetic Kill Vehicle has to be able to discriminate the reentry vehicle from the surrounding debris and decoys. - The Kinetic Kill Vehicle has to be able to implement an accurate guidance algorithm in order to perform a kinetic interception (direct collision) of the reentry vehicle, at relative speeds of more than 10 km/s. All these problems are being dealt simultaneously by the Ground-Based Missile Defense System that is developing very complex and expensive sensors, communications and control centers and long-range interceptors (Ground-Based Interceptor Missile) including a Kinetic Kill Vehicle. Among all the technical challenges involved in this interception scenario, this thesis focuses on the algorithms required for the guidance of the Interceptor Missile and the Kinetic Kill Vehicle in order to perform the direct collision with the ICBM. The involved guidance algorithms are deeply analysed in this thesis in part III where conventional guidance strategies are reviewed and optimal guidance algorithms are developed for this interception problem. The generation of a realistic simulation of the interception scenario between an ICBM and a Ground Based Interceptor designed to destroy it was considered as necessary in order to be able to compare different guidance strategies with meaningful results. As a consequence, a highly representative simulator for an ICBM and a Kill Vehicle has been implemented, as detailed in part II, and the generation of these simulators has also become one of the purposes of this thesis. In summary, the main purposes of this thesis are: - To develop a highly representative simulator of an interception scenario between an ICBM and a Kill Vehicle launched from a Ground Based Interceptor. -To analyse the main existing guidance algorithms both for the ascent phase and the terminal phase of the missiles. Novel conclusions of these analyses are obtained. - To develop original optimal guidance algorithms for the interception problem. - To compare the results obtained using the different guidance strategies, assess the behaviour of the optimal guidance algorithms, and analyse the feasibility of the Ballistic Missile Defense system in terms of guidance (part IV). As a secondary objective, a general overview of the state of the art in terms of ballistic missiles and anti-ballistic missile defence is provided (part I).