868 resultados para Robot interface


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This work proposes a fully-digital interface circuit for the measurement of inductive sensors using a low-cost microcontroller (µC) and without any intermediate active circuit. Apart from the µC and the sensor, the circuit just requires an external resistor and a reference inductance so that two RL circuits with a high-pass filter (HPF) topology are formed. The µC appropriately excites such RL circuits in order to measure the discharging time of the voltage across each inductance (i.e. sensing and reference) and then it uses such discharging times to estimate the sensor inductance. Experimental tests using a commercial µC show a non-linearity error (NLE) lower than 0.5%FSS (Full-Scale Span) when measuring inductances from 1 mH to 10 mH, and from 10 mH to 100 mH.

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Gaseous mercury sampling conditions were optimized and a dynamic flux chamber was used to measure the air/surface exchange of mercury in some areas of the Negro river basin with different vegetal coverings. At the two forest sites (flooding and non-flooding), low mercury fluxes were observed: maximum of 3 pmol m-2 h-1 - day and minimum of -1 pmol m-2 h-1 - night. At the deforested site, the mercury fluxes were higher and always positive: maximum of 26 pmol m-2 h-1 - day and 17 pmol m-2 h-1 - night. Our results showed that deforestation could be responsible for significantly increasing soil Hg emissions, mainly because of the high soil temperatures reached at deforested sites.

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In the begining of April 2004, concentrations of NHx (NH3 + NH4+) were measured in surface waters of the Guanabara Bay. Concentrations varied from 2 to 143 mmol L-1. Ammonia exchange at the air-sea interface was quantified using a numerical model. No measurement of NH3 concentration in air (c air) was performed. Thus, calculations of NH3 flux were based on the assumptions of c air = 1 and 5 µg m-3. Fluxes were predominantly from the water to the atmosphere and varied from -20 to almost 3500 µg N m-2 h-1.

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Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping

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This paper proposes the use of an autonomous assistant mobile robot in order to monitor the environmental conditions of a large indoor area and develop an ambient intelligence application. The mobile robot uses single high performance embedded sensors in order to collect and geo-reference environmental information such as ambient temperature, air velocity and orientation and gas concentration. The data collected with the assistant mobile robot is analyzed in order to detect unusual measurements or discrepancies and develop focused corrective ambient actions. This paper shows an example of the measurements performed in a research facility which have enabled the detection and location of an uncomfortable temperature profile inside an office of the research facility. The ambient intelligent application has been developed by performing some localized ambient measurements that have been analyzed in order to propose some ambient actuations to correct the uncomfortable temperature profile.

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FEMA's mission is to support our citizens and first responders to ensure that as a Nation we work together to build, sustain, and improve our capability to prepare for, protect against, respond to, recover from, and mitigate all hazards.

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A brain-computer interface (BCI) is a new communication channel between the human brain and a computer. Applications of BCI systems comprise the restoration of movements, communication and environmental control. In this study experiments were made that used the BCI system to control or to navigate in virtual environments (VE) just by thoughts. BCI experiments for navigation in VR were conducted so far with synchronous BCI and asynchronous BCI systems. The synchronous BCI analyzes the EEG patterns in a predefined time window and has 2 to 3 degrees of freedom.

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The development of load-bearing osseous implant with desired mechanical and surface properties in order to promote incorporation with bone and to eliminate risk of bone resorption and implant failure is a very challenging task. Bone formation and resoption processes depend on the mechanical environment. Certain stress/strain conditions are required to promote new bone growth and to prevent bone mass loss. Conventional metallic implants with high stiffness carry most of the load and the surrounding bone becomes virtually unloaded and inactive. Fibre-reinforced composites offer an interesting alternative to metallic implants, because their mechanical properties can be tailored to be equal to those of bone, by the careful selection of matrix polymer, type of fibres, fibre volume fraction, orientation and length. Successful load transfer at bone-implant interface requires proper fixation between the bone and implant. One promising method to promote fixation is to prepare implants with porous surface. Bone ingrowth into porous surface structure stabilises the system and improves clinical success of the implant. The experimental part of this work was focused on polymethyl methacrylate (PMMA) -based composites with dense load-bearing core and porous surface. Three-dimensionally randomly orientated chopped glass fibres were used to reinforce the composite. A method to fabricate those composites was developed by a solvent treatment technique and some characterisations concerning the functionality of the surface structure were made in vitro and in vivo. Scanning electron microscope observations revealed that the pore size and interconnective porous architecture of the surface layer of the fibre-reinforced composite (FRC) could be optimal for bone ingrowth. Microhardness measurements showed that the solvent treatment did not have an effect on the mechanical properties of the load-bearing core. A push-out test, using dental stone as a bone model material, revealed that short glass fibre-reinforced porous surface layer is strong enough to carry load. Unreacted monomers can cause the chemical necrosis of the tissue, but the levels of leachable resisidual monomers were considerably lower than those found in chemically cured fibre-reinforced dentures and in modified acrylic bone cements. Animal experiments proved that surface porous FRC implant can enhance fixation between bone and FRC. New bone ingrowth into the pores was detected and strong interlocking between bone and the implant was achieved.

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A thermodynamically consistent damage model for the simulation of progressive delamination under variable mode ratio is presented. The model is formulated in the context of the Damage Mechanics. The constitutive equation that results from the definition of the free energy as a function of a damage variable is used to model the initiation and propagation of delamination. A new delamination initiation criterion is developed to assure that the formulation can account for changes in the loading mode in a thermodynamically consistent way. The formulation proposed accounts for crack closure effets avoiding interfacial penetration of two adjacent layers aftercomplete decohesion. The model is implemented in a finite element formulation. The numerical predictions given by the model are compared with experimental results

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The decolorization and degradation of direct red 23 azo dye have been investigated in aqueous suspension of titanium dioxide under artificial irradiation. The effects of some operational parameters such as azo dye concentration, catalyst loading, and solution pH were investigated at 30.0 ºC and optimized values were obtained. The first-order kinetic model was used to discuss the results. The UV-Vis spectra changes showed that the azo dye sample, collected after 6 h irradiation, was 98% decolorized while the residual total carbon was 97.9% degraded, indicating simultaneous photodecolorization and degradation.

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La interacció home-màquina per mitjà de la veu cobreix moltes àrees d’investigació. Es destaquen entre altres, el reconeixement de la parla, la síntesis i identificació de discurs, la verificació i identificació de locutor i l’activació per veu (ordres) de sistemes robòtics. Reconèixer la parla és natural i simple per a les persones, però és un treball complex per a les màquines, pel qual existeixen diverses metodologies i tècniques, entre elles les Xarxes Neuronals. L’objectiu d’aquest treball és desenvolupar una eina en Matlab per al reconeixement i identificació de paraules pronunciades per un locutor, entre un conjunt de paraules possibles, i amb una bona fiabilitat dins d’uns marges preestablerts. El sistema és independent del locutor que pronuncia la paraula, és a dir, aquest locutor no haurà intervingut en el procés d’entrenament del sistema. S’ha dissenyat una interfície que permet l’adquisició del senyal de veu i el seu processament mitjançant xarxes neuronals i altres tècniques. Adaptant una part de control al sistema, es podria utilitzar per donar ordres a un robot com l’Alfa6Uvic o qualsevol altre dispositiu.

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Sensor-based robot control allows manipulation in dynamic environments with uncertainties. Vision is a versatile low-cost sensory modality, but low sample rate, high sensor delay and uncertain measurements limit its usability, especially in strongly dynamic environments. Force is a complementary sensory modality allowing accurate measurements of local object shape when a tooltip is in contact with the object. In multimodal sensor fusion, several sensors measuring different modalities are combined to give a more accurate estimate of the environment. As force and vision are fundamentally different sensory modalities not sharing a common representation, combining the information from these sensors is not straightforward. In this thesis, methods for fusing proprioception, force and vision together are proposed. Making assumptions of object shape and modeling the uncertainties of the sensors, the measurements can be fused together in an extended Kalman filter. The fusion of force and visual measurements makes it possible to estimate the pose of a moving target with an end-effector mounted moving camera at high rate and accuracy. The proposed approach takes the latency of the vision system into account explicitly, to provide high sample rate estimates. The estimates also allow a smooth transition from vision-based motion control to force control. The velocity of the end-effector can be controlled by estimating the distance to the target by vision and determining the velocity profile giving rapid approach and minimal force overshoot. Experiments with a 5-degree-of-freedom parallel hydraulic manipulator and a 6-degree-of-freedom serial manipulator show that integration of several sensor modalities can increase the accuracy of the measurements significantly.

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Deflection compensation of flexible boom structures in robot positioning is usually done using tables containing the magnitude of the deflection with inverse kinematics solutions of a rigid structure. The number of table values increases greatly if the working area of the boom is large and the required positioning accuracy is high. The inverse kinematics problems are very nonlinear, and if the structure is redundant, in some cases it cannot be solved in a closed form. If the structural flexibility of the manipulator arms is taken into account, the problem is almost impossible to solve using analytical methods. Neural networks offer a possibility to approximate any linear or nonlinear function. This study presents four different methods of using neural networks in the static deflection compensation and inverse kinematics solution of a flexible hydraulically driven manipulator. The training information required for training neural networks is obtained by employing a simulation model that includes elasticity characteristics. The functionality of the presented methods is tested based on the simulated and measured results of positioning accuracy. The simulated positioning accuracy is tested in 25 separate coordinate points. For each point, the positioning is tested with five different mass loads. The mean positioning error of a manipulator decreased from 31.9 mm to 4.1 mm in the test points. This accuracy enables the use of flexible manipulators in the positioning of larger objects. The measured positioning accuracy is tested in 9 separate points using three different mass loads. The mean positioning error decreased from 10.6 mm to 4.7 mm and the maximum error from 27.5 mm to 11.0 mm.

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It is necessary to use highly specialized robots in ITER (International Thermonuclear Experimental Reactor) both in the manufacturing and maintenance of the reactor due to a demanding environment. The sectors of the ITER vacuum vessel (VV) require more stringent tolerances than normally expected for the size of the structure involved. VV consists of nine sectors that are to be welded together. The vacuum vessel has a toroidal chamber structure. The task of the designed robot is to carry the welding apparatus along a path with a stringent tolerance during the assembly operation. In addition to the initial vacuum vessel assembly, after a limited running period, sectors need to be replaced for repair. Mechanisms with closed-loop kinematic chains are used in the design of robots in this work. One version is a purely parallel manipulator and another is a hybrid manipulator where the parallel and serial structures are combined. Traditional industrial robots that generally have the links actuated in series are inherently not very rigid and have poor dynamic performance in high speed and high dynamic loading conditions. Compared with open chain manipulators, parallel manipulators have high stiffness, high accuracy and a high force/torque capacity in a reduced workspace. Parallel manipulators have a mechanical architecture where all of the links are connected to the base and to the end-effector of the robot. The purpose of this thesis is to develop special parallel robots for the assembly, machining and repairing of the VV of the ITER. The process of the assembly and machining of the vacuum vessel needs a special robot. By studying the structure of the vacuum vessel, two novel parallel robots were designed and built; they have six and ten degrees of freedom driven by hydraulic cylinders and electrical servo motors. Kinematic models for the proposed robots were defined and two prototypes built. Experiments for machine cutting and laser welding with the 6-DOF robot were carried out. It was demonstrated that the parallel robots are capable of holding all necessary machining tools and welding end-effectors in all positions accurately and stably inside the vacuum vessel sector. The kinematic models appeared to be complex especially in the case of the 10-DOF robot because of its redundant structure. Multibody dynamics simulations were carried out, ensuring sufficient stiffness during the robot motion. The entire design and testing processes of the robots appeared to be complex tasks due to the high specialization of the manufacturing technology needed in the ITER reactor, while the results demonstrate the applicability of the proposed solutions quite well. The results offer not only devices but also a methodology for the assembly and repair of ITER by means of parallel robots.

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In Surface water concentrations of N2O were measured at 37 stations in Guanabara Bay and fluxes estimated across the air-sea interface. Concentrations averaged 8.2 ± 2.2 nmol L-1 and 90% of the stations showed supersaturation averaging 33%. N2O fluxes were estimated using a two-film model which is given by the product of the concentration difference across the film and the gas transfer coefficient (k w). Two parametrizations of k w were used which provided average fluxes of 0.3 and 3.0 µg N m-2 h-1. Flux measurements using floating chambers (not reported here) seem to agree with the upper limit of these estimates.