40 resultados para Obstacle avoidance
Resumo:
Much of the benefits of deploying unmanned aerial vehicles can be derived from autonomous missions. For such missions, however, sense-and-avoid capability (i.e., the ability to detect potential collisions and avoid them) is a critical requirement. Collision avoidance can be broadly classified into global and local path-planning algorithms, both of which need to be addressed in a successful mission. Whereas global path planning (which is mainly done offline) broadly lays out a path that reaches the goal point, local collision-avoidance algorithms, which are usually fast, reactive, and carried out online, ensure safety of the vehicle from unexpected and unforeseen obstacles/collisions. Even though many techniques for both global and local collision avoidance have been proposed in the recent literature, there is a great interest around the globe to solve this important problem comprehensively and efficiently and such techniques are still evolving. This paper presents a brief overview of a few promising and evolving ideas on collision avoidance for unmanned aerial vehicles, with a preferential bias toward local collision avoidance.
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In this article, several basic swarming laws for Unmanned Aerial Vehicles (UAVs) are developed for both two-dimensional (2D) plane and three-dimensional (3D) space. Effects of these basic laws on the group behaviour of swarms of UAVs are studied. It is shown that when cohesion rule is applied an equilibrium condition is reached in which all the UAVs settle at the same altitude on a circle of constant radius. It is also proved analytically that this equilibrium condition is stable for all values of velocity and acceleration. A decentralised autonomous decision-making approach that achieves collision avoidance without any central authority is also proposed in this article. Algorithms are developed with the help of these swarming laws for two types of collision avoidance, Group-wise and Individual, in 2D plane and 3D space. Effect of various parameters are studied on both types of collision avoidance schemes through extensive simulations.
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While performing a mission, multiple Unmanned Aerial Vehicles (UAVs) need to avoid each other to prevent collisions among them. In this paper, we design a collision avoidance algorithm to resolve the conflict among UAVs that are on a collision course while flying to heir respective destinations. The collision avoidance algorithm consist of each UAV that is on a collision course reactively executing a maneuver that will, as in `inverse' Proportional Navigation (PN), increase Line of Sight (LOS) rate between them, resulting in a `pulling out' of collision course. The algorithm is tested for high density traffic scenarios as well as for robustness in the presence of noise.
Resumo:
This paper addresses the problem of multiple unmanned aerial vehicle (UAV) rendezvous when the UAVs have to perform maneuvers to avoid collisions with other UAVs. The proposed solution consists of using velocity control and a wandering maneuver, if needed, of the UAVs based on a consensus among them on the estimated time of arrival at the point of the rendezvous. This algorithm, with a slight modification is shown to be useful in tracking stationary or slowly moving targets with a standoff distance. The proposed algorithm is simple and computationally efficient. The simulation results demonstrate the efficacy of the proposed approach. DOI: 10.1061/(ASCE)AS.1943-5525.0000145. (C) 2012 American Society of Civil Engineers.
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Approximately one third of the world population is infected with Mycobacterium tuberculosis, the causative agent of tuberculosis. A better understanding of the pathogen biology is crucial to develop new tools/strategies to tackle its spread and treatment. In the host macrophages, the pathogen is exposed to reactive oxygen species, known to damage dGTP and GTP to 8-oxo-dGTP and 8-oxo-GTP, respectively. Incorporation of the damaged nucleotides in nucleic acids is detrimental to organisms. MutT proteins, belonging to a class of Nudix hydrolases, hydrolyze 8-oxo-G nucleoside triphosphates/diphosphates to the corresponding nucleoside monophosphates and sanitize the nucleotide pool. Mycobacteria possess several MutT proteins. However, a functional homolog of Escherichia coli MutT has not been identified. Here, we characterized MtuMutT1 and Rv1700 proteins of M. tuberculosis. Unlike other MutT proteins, MtuMutT1 converts 8-oxo-dGTP to 8-oxo-dGDP, and 8-oxo-GTP to 8-oxo-GDP. Rv1700 then converts them to the corresponding nucleoside monophosphates. This observation suggests the presence of a two-stage mechanism of 8-oxo-dGTP/8-oxo-GTP detoxification in mycobacteria. MtuMutT1 converts 8-oxo-dGTP to 8-oxo-dGDP with a K-m of similar to 50 mu M and V-max of similar to 0.9 pmol/min per ng of protein, and Rv1700 converts 8-oxo-dGDP to 8-oxo-dGMP with a K-m of similar to 9.5 mu M and V-max of similar to 0.04 pmol/min per ng of protein. Together, MtuMutT1 and Rv1700 offer maximal rescue to E. coli for its MutT deficiency by decreasing A to C mutations (a hallmark of MutT deficiency). We suggest that the concerted action of MtuMutT1 and Rv1700 plays a crucial role in survival of bacteria against oxidative stress.
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In this article, we derive an a posteriori error estimator for various discontinuous Galerkin (DG) methods that are proposed in (Wang, Han and Cheng, SIAM J. Numer. Anal., 48: 708-733, 2010) for an elliptic obstacle problem. Using a key property of DG methods, we perform the analysis in a general framework. The error estimator we have obtained for DG methods is comparable with the estimator for the conforming Galerkin (CG) finite element method. In the analysis, we construct a non-linear smoothing function mapping DG finite element space to CG finite element space and use it as a key tool. The error estimator consists of a discrete Lagrange multiplier associated with the obstacle constraint. It is shown for non-over-penalized DG methods that the discrete Lagrange multiplier is uniformly stable on non-uniform meshes. Finally, numerical results demonstrating the performance of the error estimator are presented.
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A residual based a posteriori error estimator is derived for a quadratic finite element method (FEM) for the elliptic obstacle problem. The error estimator involves various residuals consisting of the data of the problem, discrete solution and a Lagrange multiplier related to the obstacle constraint. The choice of the discrete Lagrange multiplier yields an error estimator that is comparable with the error estimator in the case of linear FEM. Further, an a priori error estimate is derived to show that the discrete Lagrange multiplier converges at the same rate as that of the discrete solution of the obstacle problem. The numerical experiments of adaptive FEM show optimal order convergence. This demonstrates that the quadratic FEM for obstacle problem exhibits optimal performance.
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We revisit the a posteriori error analysis of discontinuous Galerkin methods for the obstacle problem derived in 25]. Under a mild assumption on the trace of obstacle, we derive a reliable a posteriori error estimator which does not involve min/max functions. A key in this approach is an auxiliary problem with discrete obstacle. Applications to various discontinuous Galerkin finite element methods are presented. Numerical experiments show that the new estimator obtained in this article performs better.
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The nonminimal coupling of a self-interacting complex scalar field with gravity is studied. For a Robertson-Walker open universe the stable solutions of the scalar-field equations are time dependent. As a result of this, a novel spontaneous symmetry breaking occurs which leads to a varying effective gravitational coupling coefficient. It is found that the coupling coefficient changes sign below a critical ‘‘radius’’ of the Universe implying the appearance of repulsive gravity. The occurrence of the repulsive interaction at an early epoch facilitates singularity avoidance. The model also provides a solution to the horizon problem.
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When a uniform flow of any nature is interrupted, the readjustment of the flow results in concentrations and rare-factions, so that the peak value of the flow parameter will be higher than that which an elementary computation would suggest. When stress flow in a structure is interrupted, there are stress concentrations. These are generally localized and often large, in relation to the values indicated by simple equilibrium calculations. With the advent of the industrial revolution, dynamic and repeated loading of materials had become commonplace in engine parts and fast moving vehicles of locomotion. This led to serious fatigue failures arising from stress concentrations. Also, many metal forming processes, fabrication techniques and weak-link type safety systems benefit substantially from the intelligent use or avoidance, as appropriate, of stress concentrations. As a result, in the last 80 years, the study and and evaluation of stress concentrations has been a primary objective in the study of solid mechanics. Exact mathematical analysis of stress concentrations in finite bodies presents considerable difficulty for all but a few problems of infinite fields, concentric annuli and the like, treated under the presumption of small deformation, linear elasticity. A whole series of techniques have been developed to deal with different classes of shapes and domains, causes and sources of concentration, material behaviour, phenomenological formulation, etc. These include real and complex functions, conformal mapping, transform techniques, integral equations, finite differences and relaxation, and, more recently, the finite element methods. With the advent of large high speed computers, development of finite element concepts and a good understanding of functional analysis, it is now, in principle, possible to obtain with economy satisfactory solutions to a whole range of concentration problems by intelligently combining theory and computer application. An example is the hybridization of continuum concepts with computer based finite element formulations. This new situation also makes possible a more direct approach to the problem of design which is the primary purpose of most engineering analyses. The trend would appear to be clear: the computer will shape the theory, analysis and design.
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Salmonella typhimurium causes an invasive disease in mice that has similarities to human typhoid. A type III protein secretion system encoded by Salmonella pathogenicity island 2 (SPI2) is essential for virulence in mice, as well as survival and multiplication within macrophages. Reactive nitrogen intermediates (RNI) synthesized by inducible nitric oxide synthase (iNOS) are involved in the control of intracellular pathogens, including S. typhimurium. We studied the effect of Salmonella infection on iNOS activity in macrophages. Immunofluorescence microscopy demonstrated efficient colocalization of iNOS with bacteria deficient in SPI2 but not wild-type Salmonella, and suggests that the SPI2 system interferes with the localization of iNOS and Salmonella. Furthermore, localization of nitrotyrosine residues in the proximity was observed for SPI2 mutant strains but not wild-type Salmonella, indicating that peroxynitrite, a potent antimicrobial compound, is excluded from Salmonella-containing vacuoles by action of SPI2. Altered colocalization of iNOS with intracellular Salmonella required the function of the SPI2-encoded type III secretion system, but not of an individual "Salmonella translocated effector." Inhibition of iNOS increased intracellular proliferation of SPI2 mutant bacteria and, to a lesser extent, of wild-type Salmonella. The defect in systemic infection of a SPI2 mutant strain was partially restored in iNOS(-/-) mice. In addition to various strategies to detoxify RNI or repair damage due to RNI, avoidance of colocalization with RNI is important in adaptation of a pathogen to an intracellular life style.
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Previous studies have shown that buffering packets in DRAM is a performance bottleneck. In order to understand the impediments in accessing the DRAM, we developed a detailed Petri net model of IP forwarding application on IXP2400 that models the different levels of the memory hierarchy. The cell based interface used to receive and transmit packets in a network processor leads to some small size DRAM accesses. Such narrow accesses to the DRAM expose the bank access latency, reducing the bandwidth that can be realized. With real traces up to 30% of the accesses are smaller than the cell size, resulting in 7.7% reduction in DRAM bandwidth. To overcome this problem, we propose buffering these small chunks of data in the on chip scratchpad memory. This scheme also exploits greater degree of parallelism between different levels of the memory hierarchy. Using real traces from the internet, we show that the transmit rate can be improved by an average of 21% over the base scheme without the use of additional hardware. Further, the impact of different traffic patterns on the network processor resources is studied. Under real traffic conditions, we show that the data bus which connects the off-chip packet buffer to the micro-engines, is the obstacle in achieving higher throughput.
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Mixed-species foraging associations may form to enhance feeding success or to avoid predators. We report the costs and consequences of an unusual foraging association between an endemic foliage gleaning tupaid (Nicobar treeshrew Tupaia nicobarica) and two species of birds; one an insectivorous commensal (greater racket-tailed drongo Dicrurus paradiseus) and the other a diurnal raptor and potential predator (Accipiter sp.). In an alliance driven, and perhaps engineered, by drongos, these species formed cohesive groups with predictable relationships. Treeshrew breeding pairs were found more frequently than solitary individuals with sparrowhawks and were more likely to tolerate sparrowhawks in the presence of drongos. Treeshrews maintained greater distances from sparrowhawks than drongos, and permitted the raptors to come closer when drongos were present. Treeshrew foraging rates declined in the presence of drongos; however, the latter may provide them predator avoidance benefits. The choice of the raptor to join the association is intriguing; particular environmental resource states may drive the evolution of such behavioural strategies. Although foraging benefits seem to be the primary driver of this association, predator avoidance also influences interactions, suggesting that strategies driving the formation of flocks may be complex and context dependent with varying benefits for different actors.
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Low-temperature plastic flow in copper was investigated by studying its tensile and creep deformation characteristics. The dependence of the flow stress on temperature and strain rate was used to evaluate the thermal activation energy while the activation area was derived from the change-in-stress creep experiments. A value of 0.6 eV was obtained for the total obstacle energy both in electrolytic and commerical copper. The activation areas in copper of three selected purities fell in the range 1200 to 100 b2. A forest intersection mechanism seems to control the temperature dependent part of the flow stress. The increase in the athermal component of the flow stress with impurity content in copper is attributed to a change in the dislocation density. The investigation also revealed that thermal activation of some attractive junctions also takes place during low-temperature creep. The model of attractive junction formation on a stress decrement during creep, yields a value of 45±10 ergs cm-2 for the stacking fault energy in copper.