926 resultados para flying robot
Estudi de comportaments socials d'aixams robòtics amb aplicació a la neteja d'espais no estructurats
Resumo:
La intel·ligència d’eixams és una branca de la intel·ligència artificial que està agafant molta força en els últims temps, especialment en el camp de la robòtica. En aquest projecte estudiarem el comportament social sorgit de les interaccions entre un nombre determinat de robots autònoms en el camp de la neteja de grans superfícies. Un cop triat un escenari i un robot que s’ajustin als requeriments del projecte, realitzarem una sèrie de simulacions a partir de diferents polítiques de cerca que ens permetran avaluar el comportament dels robots per unes condicions inicials de distribució dels robots i zones a netejar. A partir dels resultats obtinguts serem capaços de determinar quina configuració genera millors resultats.
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We use a difference-in-difference estimator to examine the effects of a merger involving three airlines. The novelty lies in the examination of this operation in two distinct scenarios: (1) on routes where two low-cost carriers and (2) on routes where a network and one of the low-cost airlines had previously been competing. We report a reduction in frequencies but no substantial effect on prices in the first scenario, while in the second we report an increase in prices but no substantial effect on frequencies. These results may be attributed to the differences in passenger types flying on these routes.
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Este proyecto surge de la iniciativa de mejorar la calidad docente de las prácticas en la asignatura Robótica y Automatización Industrial impartida en la ETSE (Escola Tècnica Superior d’Enginyeria) de la UAB, mediante un sistema innovador. El objetivo es sustituir las actuales prácticas, basadas en la realización de simulaciones en entorno MATLAB para verificar las ecuaciones que gobiernan a los robots manipuladores, por un entorno de prácticas más atractivo consistente en un robot manipulador real, que podrá ser programado para la realización de tareas de PPO (Pick and Place Operation).
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Nutritional status relating to flight activity was investigated in natural populations of Triatoma sordida and T. guasayana during the dry season in the Bolivian Chaco. The peak flight activity of both species was unimodal and covered the period 61-180 min after sunset. The weight of insects was used as the indicator of nutritional status. Interspecies comparisons employing the same sex and type of capture showed a higher weight for T. guasayana. No significant difference according to weight was observed between flying insects and those collected in natural ecotopes (hollow trees and bromeliads). More than 87% of insects collected from natural ecotopes displayed flight ability under the study conditions, explaining their tendency to invade artificial structures during the dry season.
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In Central Amazon, Brazil, the tabanid Phorcotabanus cinereus (Wiedemann) was recorded attacking the native duck Cairina moschata (Linnaeus) (Anseriformes, Anatidae). The flight and behavior of the tabanid during the attacks and the host's defenses were videotaped and analyzed in slow motion. The tabanid was recorded flying rapidly around the heads of the ducks before landing. Landing always took place on the beak, and then the tabanid walked to the fleshy caruncle on the basal part of the beak to bite and feed. Firstly the duck defends itself through lateral harsh head movements, and then, when it is being bitten, it defends itself by rubbing its head on the body, or dipping the head into water, when swimming. If disturbed, the fly resumed the same pattern of flight as before and would generally try to land again on the same host and bite in the same place. This feeding activity was observed predominantly between 9:30 am and 4:30 pm and always in open areas, near aquatic environments, from June 1996 to January 1997, the dry season in Central Amazon. To test the attractiveness of other animals to P. cinereus, mammals, caimans and domestic and wild birds were placed in suitable habitat and the response of P. cinereus observed. P. cinereus did not attack these animals, suggesting that this species has a preference for ducks, which are plentiful in the region.
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Epidemiological studies of malaria or other vector-transmitted diseases often consider vectors as passive actors in the complex life cycle of the parasites, assuming that vector populations are homogeneous and vertebrate hosts are equally susceptible to being infected during their lifetime. However, some studies based on both human and rodent malaria systems found that mosquito vectors preferentially selected infected vertebrate hosts. This subject has been scarcely investigated in avian malaria models and even less in wild animals using natural host-parasite associations. We investigated whether the malaria infection status of wild great tits, Parus major, played a role in host selection by the mosquito vector Culex pipiens. Pairs of infected and uninfected birds were tested in a dual-choice olfactometer to assess their attractiveness to the mosquitoes. Plasmodium-infected birds attracted significantly fewer mosquitoes than the uninfected ones, which suggest that avian malaria parasites alter hosts' odours involved in vector orientation. Reaction time of the mosquitoes, that is, the time taken to select a host, and activation of mosquitoes, defined as the proportion of individuals flying towards one of the hosts, were not affected by the bird's infection status. The importance of these behavioural responses for the vector is discussed in light of recent advances in related or similar model systems.
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Feathers confer protection against biophysical agents and determine flying ability. The geometry and arrangement of the barbs, together with the keratin and pigments deposited in the feathers, determine the mechanical stability of the vane, and its stiffness and resistance to abrasive agents. In colour-polymorphic species, individuals display alternative colour morphs, which can be associated with different foraging strategies. Each morph may therefore require specific flying abilities, and their feathers may be exposed to different abrasive agents. Feathers of differently coloured individuals may thus have a specific structure, and colour pigments may help resist abrasive agents and improve stiffness. We examined these predictions in the barn owl (Tyto alba), a species for which the ventral body side varies from white to dark reddish pheomelanic, and in the number and size of black spots located at the tip of the feathers. White and reddish birds show different foraging strategies, and the size of black feather spots is associated with several phenotypic attributes. We found that birds displaying a darker reddish coloration on the ventral body side deposit more melanin pigments in their remiges, which also have fewer barbs. This suggests that wear resistance increases with darkness, whereas feathers of lighter coloured birds may bend less easily. Accordingly, individuals displaying a lighter reddish coloration on the ventral body side, and those displaying larger black spots, displayed more black transverse bars on their remiges: as larger-spotted individuals are heavier and longer-winged birds also have more transverse bars, these bars may reduce feather bending when flying. We conclude that differently coloured individuals produce wing feathers of different strengths to adopt alternative behavioural and life history strategies
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This paper proposes a field application of a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot in cable tracking task. The learning system is characterized by using a direct policy search method for learning the internal state/action mapping. Policy only algorithms may suffer from long convergence times when dealing with real robotics. In order to speed up the process, the learning phase has been carried out in a simulated environment and, in a second step, the policy has been transferred and tested successfully on a real robot. Future steps plan to continue the learning process on-line while on the real robot while performing the mentioned task. We demonstrate its feasibility with real experiments on the underwater robot ICTINEU AUV
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Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task
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When underwater vehicles navigate close to the ocean floor, computer vision techniques can be applied to obtain motion estimates. A complete system to create visual mosaics of the seabed is described in this paper. Unfortunately, the accuracy of the constructed mosaic is difficult to evaluate. The use of a laboratory setup to obtain an accurate error measurement is proposed. The system consists on a robot arm carrying a downward looking camera. A pattern formed by a white background and a matrix of black dots uniformly distributed along the surveyed scene is used to find the exact image registration parameters. When the robot executes a trajectory (simulating the motion of a submersible), an image sequence is acquired by the camera. The estimated motion computed from the encoders of the robot is refined by detecting, to subpixel accuracy, the black dots of the image sequence, and computing the 2D projective transform which relates two consecutive images. The pattern is then substituted by a poster of the sea floor and the trajectory is executed again, acquiring the image sequence used to test the accuracy of the mosaicking system
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This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory
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This paper presents an approach to ameliorate the reliability of the correspondence points relating two consecutive images of a sequence. The images are especially difficult to handle, since they have been acquired by a camera looking at the sea floor while carried by an underwater robot. Underwater images are usually difficult to process due to light absorption, changing image radiance and lack of well-defined features. A new approach based on gray-level region matching and selective texture analysis significantly improves the matching reliability
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This paper proposes MSISpIC, a probabilistic sonar scan matching algorithm for the localization of an autonomous underwater vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), the robot displacement estimated through dead-reckoning using a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method is an extension of the pIC algorithm. An extended Kalman filter (EKF) is used to estimate the robot-path during the scan in order to reference all the range and bearing measurements as well as their uncertainty to a scan fixed frame before registering. The major contribution consists of experimentally proving that probabilistic sonar scan matching techniques have the potential to improve the DVL-based navigation. The algorithm has been tested on an AUV guided along a 600 m path within an abandoned marina underwater environment with satisfactory results
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This paper proposes a parallel architecture for estimation of the motion of an underwater robot. It is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. In a motion estimation algorithm, correspondences between two images have to be solved at the low level. In the underwater imaging, normalised correlation can be a solution in the presence of non-uniform illumination. Due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. Taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed