38 resultados para haptic motion control


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A novel method for controlling wave energy converters using active bipolar damping is described and compared with current control methods. The performance of active bipolar damping is modelled numerically for two distinct types of wave energy converter and it is found that in both cases the power capture can be significantly increased relative to optimal linear damping. It is shown that this is because active bipolar damping has the potential for providing a quasi-spring or quasi-inertia, which improves the wave energy converter's tuning and amplitude of motion, resulting in the increase in power capture observed. The practical implementation of active bipolar damping is also discussed. It is noted that active bipolar damping does not require a reactive energy store and thereby reduces the cost and eliminates losses due to the cycling of reactive energy. It is also noted that active bipolar damping could be implemented using a single constant pressure double-acting hydraulic cylinder and so potentially represents a simple, efficient, robust and economic solution to the control of wave energy converters.

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A new domain-specific, reconfigurable system-on-a-chip (SoC) architecture is proposed for video motion estimation. This has been designed to cover most of the common block-based video coding standards, including MPEG-2, MPEG-4, H.264, WMV-9 and AVS. The architecture exhibits simple control, high throughput and relatively low hardware cost when compared with existing circuits. It can also easily handle flexible search ranges without any increase in silicon area and can be configured prior to the start of the motion estimation process for a specific standard. The computational rates achieved make the circuit suitable for high-end video processing applications, such as HDTV. Silicon design studies indicate that circuits based on this approach incur only a relatively small penalty in terms of power dissipation and silicon area when compared with implementations for specific standards. Indeed, the cost/performance achieved exceeds that of existing but specific solutions and greatly exceeds that of general purpose field programmable gate array (FPGA) designs.

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By means of optimal control techniques we model and optimize the manipulation of the external quantum state (center-of-mass motion) of atoms trapped in adjustable optical potentials. We consider in detail the cases of both noninteracting and interacting atoms moving between neighboring sites in a lattice of a double-well optical potentials. Such a lattice can perform interaction-mediated entanglement of atom pairs and can realize two-qubit quantum gates. The optimized control sequences for the optical potential allow transport faster and with significantly larger fidelity than is possible with processes based on adiabatic transport.

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The cerebral cortex contains circuitry for continuously computing properties of the environment and one's body, as well as relations among those properties. The success of complex perceptuomotor performances requires integrated, simultaneous use of such relational information. Ball catching is a good example as it involves reaching and grasping of visually pursued objects that move relative to the catcher. Although integrated neural control of catching has received sparse attention in the neuroscience literature, behavioral observations have led to the identification of control principles that may be embodied in the involved neural circuits. Here, we report a catching experiment that refines those principles via a novel manipulation. Visual field motion was used to perturb velocity information about balls traveling on various trajectories relative to a seated catcher, with various initial hand positions. The experiment produced evidence for a continuous, prospective catching strategy, in which hand movements are planned based on gaze-centered ball velocity and ball position information. Such a strategy was implemented in a new neural model, which suggests how position, velocity, and temporal information streams combine to shape catching movements. The model accurately reproduces the main and interaction effects found in the behavioral experiment and provides an interpretation of recently observed target motion-related activity in the motor cortex during interceptive reaching by monkeys. It functionally interprets a broad range of neurobiological and behavioral data, and thus contributes to a unified theory of the neural control of reaching to stationary and moving targets.

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Two prospective controllers of hand movements in catching-both based on required velocity control-were simulated. Under certain conditions, this required velocity control led to overshoots of the future interception point. These overshoots were absent in pertinent experiments. To remedy this shortcoming, the required velocity model was reformulated in terms of a neural network, the Vector Integration To Endpoint model, to create a Required Velocity Integration To Endpoint model. Addition of a parallel relative velocity channel, resulting in the Relative and Required Velocity Integration To Endpoint model, provided a better account for the experimentally observed kinematics than the existing, purely behavioral models. Simulations of reaching to intercept decelerating and accelerating objects in the presence of background motion were performed to make distinct predictions for future experiments.

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In this paper, a new reconfigurable multi-standard architecture is introduced for integer-pixel motion estimation and a standard-cell based chip design study is presented. This has been designed to cover most of the common block-based video compression standards, including MPEG-2, MPEG-4, H.263, H.264, AVS and WMV-9. The architecture exhibits simpler control, high throughput and relative low hardware cost and highly competitive when compared with excising designs for specific video standards. It can also, through the use of control signals, be dynamically reconfigured at run-time to accommodate different system constraint such as the trade-off in power dissipation and video-quality. The computational rates achieved make the circuit suitable for high end video processing applications. Silicon design studies indicate that circuits based on this approach incur only a relatively small penalty in terms of power dissipation and silicon area when compared with implementations for specific standards.

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Development of magnetoelectric, electromechanical, and photovoltaic devices based on mixed-phase rhombohedral-tetragonal (R-T) BiFeO3 (BFO) systems is possible only if the control of the engineered R phase variants is realized. Accordingly, we explore the mechanism of a bias induced phase transformation in this system. Single point spectroscopy demonstrates that the T -> R transition is activated at lower voltages compared to T -> - T polarization switching. With phase field modeling, the transition is shown to be electrically driven. We further demonstrate that symmetry of formed R-phase rosettes can be broken by a proximal probe motion, allowing controlled creation of R variants with defined orientation. This approach opens a pathway to designing next-generation magnetoelectronic and data storage devices in the nanoscale.

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Manual interception, such as catching or hitting an approaching ball, requires the hand to contact a moving object at the right location and at the right time. Many studies have examined the neural mechanisms underlying the spatial aspects of goal-directed reaching, but the neural basis of the spatial and temporal aspects of manual interception are largely unknown. Here, we used repetitive transcranial magnetic stimulation (rTMS) to investigate the role of the human middle temporal visual motion area (MT+/V5) and superior parieto-occipital cortex (SPOC) in the spatial and temporal control of manual interception. Participants were required to reach-to-intercept a downward moving visual target that followed an unpredictably curved trajectory, presented on a screen in the vertical plane. We found that rTMS to MT+/V5 influenced interceptive timing and positioning, whereas rTMS to SPOC only tended to increase the spatial variance in reach end points for selected target trajectories. These findings are consistent with theories arguing that distinct neural mechanisms contribute to spatial, temporal, and spatiotemporal control of manual interception.

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Manipulator motion planning is a task which relies heavily on the construction of a configuration space prior to path planning. However when fast real-time motion is needed, the full construction of the manipulator's high-dimensional configu-ration space can be too slow and expensive. Alternative planning methods, which avoid this full construction of the manipulator's configuration space are needed to solve this problem. Here, one such existing local planning method for manipulators based on configuration-sampling and subgoal-selection has been extended. Using a modified Artificial Potential Fields (APF) function, goal-configuration sampling and a novel subgoal selection method, it provides faster, more optimal paths than the previously proposed work. Simulation results show a decrease in both runtime and path lengths, along with a decrease in unexpected local minimum and crashing issues.

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Paradoxical kinesia describes the motor improvement in Parkinson's disease (PD) triggered by the presence of external sensory information relevant for the movement. This phenomenon has been puzzling scientists for over 60 years, both in neurological and motor control research, with the underpinning mechanism still being the subject of fierce debate. In this paper we present novel evidence supporting the idea that the key to understanding paradoxical kinesia lies in both spatial and temporal information conveyed by the cues and the coupling between perception and action. We tested a group of 7 idiopathic PD patients in an upper limb mediolateral movement task. Movements were performed with and without a visual point light display, travelling at 3 different speeds. The dynamic information presented in the visual point light display depicted three different movement speeds of the same amplitude performed by a healthy adult. The displays were tested and validated on a group of neurologically healthy participants before being tested on the PD group. Our data show that the temporal aspects of the movement (kinematics) in PD can be moderated by the prescribed temporal information presented in a dynamic environmental cue. Patients demonstrated a significant improvement in terms of movement time and peak velocity when executing movement in accordance with the information afforded by the point light display, compared to when the movement of the same amplitude and direction was performed without the display. In all patients we observed the effect of paradoxical kinesia, with a strong relationship between the perceptual information prescribed by the biological motion display and the observed motor performance of the patients. © 2013 Elsevier B.V. All rights reserved.

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A linear hydrodynamic model is used to assess the sensitivity of the performance of a wave energy converter (WEC) array to control parameters. It is found that WEC arrays have a much smaller tolerance to imprecision of the control parameters than isolated WECs and that the increase in power capture of WEC arrays is only achieved with larger amplitudes of motion of the individual WECs. The WEC array radiation pattern is found to provide useful insight into the array hydrodynamics. The linear hydrodynamic model is used, together with the wave climate at the European Marine Energy Centre (EMEC), to assess the maximum annual average power capture of a WEC array. It is found that the maximum annual average power capture is significantly reduced compared to the maximum power capture for regular waves and that the optimum array configuration is also significantly modified. It is concluded that the optimum configuration of a WEC array will be as much influenced by factors such as mooring layout, device access and power smoothing as it is by the theoretical optimum hydrodynamic configuration. © 2009 Elsevier Ltd.