986 resultados para Orbital robotics


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The lowest allowed electronic transition of fac-[Re(Cl)(CO)(3)(bopy)(2)] (bopy = 4-benzoylpyridine) has a Re --> bopy MLCT character, as revealed by UV-vis and stationary resonance Raman spectroscopy. Accordingly, the lowest-lying, long-lived, excited state is Re --> bopy (MLCT)-M-3. Electronic depopulation of the Re(CO)(3) unit and population of a bopy pi* orbital upon excitation are evident by the upward shift of v(Cequivalent toO) vibrations and a downward shift of the ketone v(C=O) vibration, respectively, seen in picosecond time-resolved IR spectra. Moreover, reduction of a single bopy ligand in the (MLCT)-M-3 excited state is indicated by time-resolved visible and resonance Raman (TR3) spectra that show features typical of bopy(.-). In contrast, the lowest allowed electronic transition and lowest-lying excited state of a new complex fac-[Re(bopy)(CO)(3)(bpy)](+) (bpy = 2,2'-bipyridine) have been identified as Re --> bpy MLCT with no involvement of the bopy ligand, despite the fact that the first reduction of this complex is bopy-localized, as was proven spectroelectrochemically. This is a rare case in which the localizations of the lowest MLCT excitation and the first reduction are different. (MLCT)-M-3 excited states of both fac-[Re(Cl)(CO)(3)(bopy)(2)] and fac-[Re(bopy)(CO)(3)(bpy)](+) are initially formed vibrationally hot. Their relaxation is manifested by picosecond dynamic shifts of v(Cequivalent toO) IR bands. The X-ray structure of fac-[Re(bopy)(CO)(3)(bpy)](PF6CH3CN)-C-. has been determined.

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This article looks at the use of cultured neural networks as the decision-making mechanism of a control system. In this case biological neurons are grown and trained to act as an artificial intelligence engine. Such research has immediate medical implications as well as enormous potential in computing and robotics. An experimental system involving closed-loop control of a mobile robot by a culture of neurons has been successfully created and is described here. This article gives a brief overview of the problem area and ongoing research. Questions are asked as to where this will lead in the future.

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The work reported in this paper is motivated towards the development of a mathematical model for swarm systems based on macroscopic primitives. A pattern formation and transformation model is proposed. The pattern transformation model comprises two general methods for pattern transformation, namely a macroscopic transformation method and a mathematical transformation method. The problem of transformation is formally expressed and four special cases of transformation are considered. Simulations to confirm the feasibility of the proposed models and transformation methods are presented. Comparison between the two transformation methods is also reported.

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Self-organizing neural networks have been implemented in a wide range of application areas such as speech processing, image processing, optimization and robotics. Recent variations to the basic model proposed by the authors enable it to order state space using a subset of the input vector and to apply a local adaptation procedure that does not rely on a predefined test duration limit. Both these variations have been incorporated into a new feature map architecture that forms an integral part of an Hybrid Learning System (HLS) based on a genetic-based classifier system. Problems are represented within HLS as objects characterized by environmental features. Objects controlled by the system have preset targets set against a subset of their features. The system's objective is to achieve these targets by evolving a behavioural repertoire that efficiently explores and exploits the problem environment. Feature maps encode two types of knowledge within HLS — long-term memory traces of useful regularities within the environment and the classifier performance data calibrated against an object's feature states and targets. Self-organization of these networks constitutes non-genetic-based (experience-driven) learning within HLS. This paper presents a description of the HLS architecture and an analysis of the modified feature map implementing associative memory. Initial results are presented that demonstrate the behaviour of the system on a simple control task.

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The winter climate of Europe and the Mediterranean is dominated by the weather systems of the mid-latitude storm tracks. The behaviour of the storm tracks is highly variable, particularly in the eastern North Atlantic, and has a profound impact on the hydroclimate of the Mediterranean region. A deeper understanding of the storm tracks and the factors that drive them is therefore crucial for interpreting past changes in Mediterranean climate and the civilizations it has supported over the last 12 000 years (broadly the Holocene period). This paper presents a discussion of how changes in climate forcing (e.g. orbital variations, greenhouse gases, ice sheet cover) may have impacted on the ‘basic ingredients’ controlling the mid-latitude storm tracks over the North Atlantic and the Mediterranean on intermillennial time scales. Idealized simulations using the HadAM3 atmospheric general circulation model (GCM) are used to explore the basic processes, while a series of timeslice simulations from a similar atmospheric GCM coupled to a thermodynamic slab ocean (HadSM3) are examined to identify the impact these drivers have on the storm track during the Holocene. The results suggest that the North Atlantic storm track has moved northward and strengthened with time since the Early to Mid-Holocene. In contrast, the Mediterranean storm track may have weakened over the same period. It is, however, emphasized that much remains still to be understood about the evolution of the North Atlantic and Mediterranean storm tracks during the Holocene period.

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In this paper we report the degree of reliability of image sequences taken by off-the-shelf TV cameras for modeling camera rotation and reconstructing 3D structure using computer vision techniques. This is done in spite of the fact that computer vision systems usually use imaging devices that are specifically designed for the human vision. Our scenario consists of a static scene and a mobile camera moving through the scene. The scene is any long axial building dominated by features along the three principal orientations and with at least one wall containing prominent repetitive planar features such as doors, windows bricks etc. The camera is an ordinary commercial camcorder moving along the axial axis of the scene and is allowed to rotate freely within the range +/- 10 degrees in all directions. This makes it possible that the camera be held by a walking unprofessional cameraman with normal gait, or to be mounted on a mobile robot. The system has been tested successfully on sequence of images of a variety of structured, but fairly cluttered scenes taken by different walking cameramen. The potential application areas of the system include medicine, robotics and photogrammetry.

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This paper presents recent developments to a vision-based traffic surveillance system which relies extensively on the use of geometrical and scene context. Firstly, a highly parametrised 3-D model is reported, able to adopt the shape of a wide variety of different classes of vehicle (e.g. cars, vans, buses etc.), and its subsequent specialisation to a generic car class which accounts for commonly encountered types of car (including saloon, batchback and estate cars). Sample data collected from video images, by means of an interactive tool, have been subjected to principal component analysis (PCA) to define a deformable model having 6 degrees of freedom. Secondly, a new pose refinement technique using “active” models is described, able to recover both the pose of a rigid object, and the structure of a deformable model; an assessment of its performance is examined in comparison with previously reported “passive” model-based techniques in the context of traffic surveillance. The new method is more stable, and requires fewer iterations, especially when the number of free parameters increases, but shows somewhat poorer convergence. Typical applications for this work include robot surveillance and navigation tasks.

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Smooth trajectories are essential for safe interaction in between human and a haptic interface. Different methods and strategies have been introduced to create such smooth trajectories. This paper studies the creation of human-like movements in haptic interfaces, based on the study of human arm motion. These motions are intended to retrain the upper limb movements of patients that lose manipulation functions following stroke. We present a model that uses higher degree polynomials to define a trajectory and control the robot arm to achieve minimum jerk movements. It also studies different methods that can be driven from polynomials to create more realistic human-like movements for therapeutic purposes.

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This paper outlines some rehabilitation applications of manipulators and identifies that new approaches demand that the robot make an intimate contact with the user. Design of new generations of manipulators with programmable compliance along with higher level controllers that can set the compliance appropriately for the task, are both feasible propositions. We must thus gain a greater insight into the way in which a person interacts with a machine, particularly given that the interaction may be non-passive. We are primarily interested in the change in wrist and arm dynamics as the person co-contracts his/her muscles. It is observed that this leads to a change in stiffness that can push an actuated interface into a limit cycle. We use both experimental results gathered from a PHANToM haptic interface and a mathematical model to observe this effect. Results are relevant to the fields of rehabilitation and therapy robots, haptic interfaces, and telerobotics

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The rigid [6]ferrocenophane, L-1, was synthesised by condensation of 1,1'-ferrocene dicarbaldehyde with trans-1,2-diaminocyclohexane in high dilution at r.t. followed by reduction. When other experimental conditions were employed, the [6,6,6]ferrocenephane (L-2) was also obtained. Both compounds were characterised by single crystal X-ray crystallography. The protonation of L-1 and its metal complexation were evaluated by the effect on the electron-transfer process of the ferrocene (fc) unit of L-1 using cyclic voltammetry (CV) and square wave voltammetry (SWV) in anhydrous CH3CN solution and in 0.1 M (Bu4NPF6)-Bu-n as the supporting electrolyte. The electrochemical process of L-1 between 300 and 900 mV is complicated by amine oxidation. On the other hand, an anodic shift from the fc/fc(+) wave of L-1 of 249, 225, 81 and 61 mV was observed by formation of Zn2+, Ni2+, Pd2+ and Cu2+ complexes, respectively. Whereas Mg2+ and Ca2+ only have with L-1 weak interactions and they promote the acid-base equilibrium of L-1. This reveals that L-1 is an interesting molecular redox sensor for detection of Zn2+ and Ni2+, although the kinetics of the Zn2+ complex formation is much faster than that of the Ni2+ one. The X-ray crystal structure of [(PdLCl2)-Cl-1] was determined and showed a square-planar environment with Pd(II) and Fe(II) centres separated by 3.781(1) angstrom. The experimental anodic shifts were elucidated by DFT calculations on the [(MLCl2)-Cl-1] series and they are related to the nature of the HOMO of these complexes and a four-electron, two-orbital interaction.