Various haptic displays are becoming available for implementing a new kind of human computer interaction (HCI) method. Among many types and models, touch panel displays have been used in wide variety of applications a...
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Various haptic displays are becoming available for implementing a new kind of human computer interaction (HCI) method. Among many types and models, touch panel displays have been used in wide variety of applications and are proven to be a useful interface infrastructure. In spite of their popularity, there are some weak points. The most serious drawback is their hardness to operate especially for the weak users in information technology such as the elderly and blind users. The tactile feedback function has a potential ability for enabling the weak to make full use of the devices. We propose an approach for effectively designing user-friendly haptic applications especially targeted at supporting the weak users. We exemplify our approach through the design and development of an electronic voting system. The system uses a touch panel haptic display for helping the weak to operate with straightforward touch sensations. It allows them to easily confirm, select, and vote their supporting candidate without any assisters. We also conducted a preliminary evaluation to verify the effectiveness of the system.
In this paper, a control mechanism is presented to improve the compliance performance of the robot manipulator when it is in contact with the unknown environment. This mechanism guarantees that the dynamics of the who...
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ISBN:
(纸本)9781424454471
In this paper, a control mechanism is presented to improve the compliance performance of the robot manipulator when it is in contact with the unknown environment. This mechanism guarantees that the dynamics of the whole system follows a target impedance model so that the desired compliance performance is obtained. In particular, under the assumption that the dynamics is periodic, a learning law is developed to estimate the unknown dynamics parameters. Besides, the proposed systematic learning control does not require the accurate force measurement. Its performance and robustness are discussed in details by the rigorous analysis. At last, the validity of the proposed method is verified by simulation.
In speech communication, humans are able to perceive not only the acoustic features but also the articulation state from speech sounds. Some specific articulation configurations can carry certain non-linguistic inform...
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In speech communication, humans are able to perceive not only the acoustic features but also the articulation state from speech sounds. Some specific articulation configurations can carry certain non-linguistic information such as emotion. However, the relation between articulation and acoustic features is still not clear. To clarify such a relation, we analyzed speech data from the emotions of cold anger and hot anger based on an emotional speech corpus and attempt to realize the observations using a physiological articulatory model. We measured the changes in acoustic features when altering articulation states for individual speech organs using the physiological articulatory model. It is found that the cold and hot angers both have emphasized components in high-frequency region, while the former controls articulation and the latter controls the sound source of the speech production system.
This paper addresses the problem of output tracking control for a class of nonlinear distributed time-delay systems whose control gains are delay-dependent and whose uncertainty involves both delay times and system no...
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This paper addresses the problem of output tracking control for a class of nonlinear distributed time-delay systems whose control gains are delay-dependent and whose uncertainty involves both delay times and system nonlinearities. We introduce the framework of using delay-independent control to deal with unknown distributed delay dependence and using switching-based adaptive neural control to deal with unknown delay-dependent control gains. The control is designed in consideration of a Razumikhin norm condition on retarded functional state entailing efficiency with distributed delay dependence.
Measurement based quantum computation, which requires only single particle measurements on a universal resource state to achieve the full power of quantum computing, has been recognized as one of the most promising mo...
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Measurement based quantum computation, which requires only single particle measurements on a universal resource state to achieve the full power of quantum computing, has been recognized as one of the most promising models for the physical realization of quantum computers. Despite considerable progress in the past decade, it remains a great challenge to search for new universal resource states with naturally occurring Hamiltonians and to better understand the entanglement structure of these kinds of states. Here we show that most of the resource states currently known can be reduced to the cluster state, the first known universal resource state, via adaptive local measurements at a constant cost. This new quantum state reduction scheme provides simpler proofs of universality of resource states and opens up plenty of space to the search of new resource states.
This paper firstly addresses the convergence analysis of iterative learning control of a class of fractional order nonlinear systems using the generalized Gronwall-Bellman lemma. Detailed problem definition and conver...
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This paper firstly addresses the convergence analysis of iterative learning control of a class of fractional order nonlinear systems using the generalized Gronwall-Bellman lemma. Detailed problem definition and convergence proof are presented together with an agenda for future research efforts.
An action of genetic algorithm could be represented in the search space as a random Markovian process. The question concerning its asymptotic stability properties is discussed. Conditions under which genetic algorithm...
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An action of genetic algorithm could be represented in the search space as a random Markovian process. The question concerning its asymptotic stability properties is discussed. Conditions under which genetic algorithm is convergent, are formulated. Then the existence of an operator to which infinite long iterations of the genetic algorithms tend, is shown. This operator describes optimal genetic algorithm in probabilistic sense.
A novel rotary nanomotor is described using two axially aligned, opposing chirality nanotube shuttles. Based on inter-shell screw-like motion of nanotubes, rotary motion is generated by electrostatically pulling the t...
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A novel rotary nanomotor is described using two axially aligned, opposing chirality nanotube shuttles. Based on inter-shell screw-like motion of nanotubes, rotary motion is generated by electrostatically pulling the two cores together. Simulations using molecular dynamics show the generation of rotation from armchair nanotube pairs and their actuation properties. The simulation results, together with recently reported progress in realizing batch-fabricated ultra-high density nanotube shuttles, point towards the use of these motors as building blocks in nanoelectromechanical systems (NEMS) and nanorobotic systems for sensing, actuation, and computation applications.
In this paper, the grasp operation of an underactuated finger mechanism is simulated with the aim to characterize and analyze its performance. The design of the proposed mechanism is based on spring systems that give ...
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In this paper, the grasp operation of an underactuated finger mechanism is simulated with the aim to characterize and analyze its performance. The design of the proposed mechanism is based on spring systems that give suitable underactuation characteristics. A CAD model is proposed and then it is used in a procedure for numerical simulation. Simulation results show suitable capability for grasping a wide range of objects in size and shape by operating the mechanism inside the finger body. The achieved grasp has been simulated as a human-like functionality with a grasp contact in each phalanx.
Accurate and effective parameter identification is an important engineering task in high performance control system design. One emerging approach to effectively identify such nonlinear or dynamic unknown parameters is...
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ISBN:
(纸本)9789746724913
Accurate and effective parameter identification is an important engineering task in high performance control system design. One emerging approach to effectively identify such nonlinear or dynamic unknown parameters is to use Particle Swarm Optimization (PSO) algorithm. Linear Permanent Magnet (LPM) motor is a high performance actuator employed in many applications that require direct linear motion without mechanical transmission for high acceleration and accurate positioning. Therefore, accurate motor parameters are necessary to effectively control the LPM motors. This paper proposes a simple PSO based method with chirp inputs to identify the LPM motor's parameters. The simulations and experiments are conducted to verify the results and determine the effectiveness of the proposed method.
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