This paper proposes a methodology based on Inertial Measurement Units (IMU's) and sensor fusion for the trajectory tracking performed by a human expert, estimating orientation in two dimensions and position in thr...
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This paper proposes a methodology based on Inertial Measurement Units (IMU's) and sensor fusion for the trajectory tracking performed by a human expert, estimating orientation in two dimensions and position in three dimensions. In addition, involving modeling of robot manipulators and the acquired trajectory, a kinematic control is generated for the robot programming. Experimental results have shown that this method is capable of acquire the trajectory performed by a human without the use of expensive Computational Video Systems (SVC's).
The main objective of this study is to provide a motion retargeting method for mapping the human motion to the humanoid robot. This paper describes the procedure to generate human-like upper limbs motion of a humanoid...
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The main objective of this study is to provide a motion retargeting method for mapping the human motion to the humanoid robot. This paper describes the procedure to generate human-like upper limbs motion of a humanoid robot while maintaining balance. The human motions are acquired by the inertial measurement units (IMU). The motion retargeting method is implemented with four steps: kinematics modelling, inverse kinematics computation, enforcing constraints and difference optimization. Our method integrates multiply existing mature technologies to build a human-robot interaction system to imitate the human motion on a robot. Finally, the method is verified on a humanoid robot Nao to generate a human-like motion. Experimental results demonstrate that the method achieves a good kinematic match.
For slender and lightweight structures, the vibration serviceability under crowd- induced loading is often critical in design. Currently, designers rely on equivalent load models, upscaled from single-person force mea...
For slender and lightweight structures, the vibration serviceability under crowd- induced loading is often critical in design. Currently, designers rely on equivalent load models, upscaled from single-person force measurements. Furthermore, it is important to consider the mechanical interaction with the human body as this can significantly reduce the structural response. To account for these interaction effects, the contact force between the pedestrian and the structure can be modelled as the superposition of the force induced by the pedestrian on a rigid floor and the force resulting from the mechanical interaction between the structure and the human body. For the case of large crowds, however, this approach leads to models with a very high system order. In the present contribution, two equivalent reduced-order models are proposed to approximate the dynamic behaviour of the full-order coupled crowd-structure system. A numerical study is performed to evaluate the impact of the modelling assumptions on the structural response to pedestrian excitation. The results show that the full-order moving crowd model can be well approximated by a reduced-order model whereby the interaction with the pedestrians in the crowd is modelled using a single (equivalent) SDOF system.
In this paper a nano-swimmer with length between 10 to 100nm consisting of a motor, filament and hinged boundaries is controlled by mathematical simulations successfully. A nano-swimmer that lies in a heterodimer magn...
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ISBN:
(纸本)9781467393522
In this paper a nano-swimmer with length between 10 to 100nm consisting of a motor, filament and hinged boundaries is controlled by mathematical simulations successfully. A nano-swimmer that lies in a heterodimer magnetic nano-particle is proposed based on existed nano-robots. Dynamic of swimming is simulated by using some sequence of shape changes where magnetic forces act on one-ends of nano-swimmer. This idea is applied to simulate drug delivery from specific point of human body to the targeted point where it is assumed transport drug lies in a nano-particle. Here, the hyper-diffusion equation that is a fourth order partial differential equation is proposed to model swimming at nano-scale. The unknown control function (magnetic force) that acts on the boundary is calculated to minimize the drug delivery energy cost. Two novel algorithms for the computation of optimal boundary control and estimation of its error function are proposed. Shape function deformations for the elastic tail of the nano-swimmer for various finite times are depicted. Numerical results for the control function for the nano-scale drug deliver are presented.
Layers of Protection Analysis (LOPA) described in the IEC 61511 standard is one of the most popular methods that enables the adequacy of the layers of protection for an industrial process to be assessed. LOPA has foun...
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Layers of Protection Analysis (LOPA) described in the IEC 61511 standard is one of the most popular methods that enables the adequacy of the layers of protection for an industrial process to be assessed. LOPA has found much broader application as a relatively simple risk assessment methodology. However, an important issue faced by risk analysts is how to deal with uncertainties that arise in the elements of the accident scenario like the severity of consequences, frequency data for initiating event, probability of failure of independent protection layers (IPL) and human reliability. (ICAT'14). This paper presents an approach of fuzzy LOPA which takes into account uncertain and/or vague data. A possibilistic representation of data by fuzzy intervals is proposed. Consequence reduced frequency is computed by extended multiplication using a-cuts method. The proposed approach is illustrated by an application to the protection of an operational system which is a heater.
In high risk forms, human papillomaviruses (HPV) can either induce or promote cancerous lesions, especially cervical cancer which is considered the second most common cancer in the women worldwide. HPV life cycle is t...
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ISBN:
(纸本)9781424492695
In high risk forms, human papillomaviruses (HPV) can either induce or promote cancerous lesions, especially cervical cancer which is considered the second most common cancer in the women worldwide. HPV life cycle is tightly linked to the infected cell differentiation program and its evolution is strictly joined to the switch between the early and the late viral polycistronic promoters. The aim of this study is to develop a novel mathematical model which collects and structures the available biologic knowledge on the early promoter regulation for HPV in episomal form. The model includes the main regulation by E_2 viral protein as well as a novel discovered co-regulation function mediated by the viral E1 protein. Only by including both E_2 and E1 regulatory effect the model is able to correctly predict the temporal behaviour of the early promoter switching off. A possible use of the model as in silico tool to evaluate new antiviral therapies is discussed.
In this paper, a method for fusing data relevant both to drivers' experience and provided information about travel time is presented. The method takes into account the "compatibility" of data originating...
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In this paper, a method for fusing data relevant both to drivers' experience and provided information about travel time is presented. The method takes into account the "compatibility" of data originating from different sources, and provides information about acceptability of results. The influence of uncertainty on drivers' compliance with provided information is examined in detail, according to the Uncertainty-based Information Theory. The data fusion results then in an updating of the expected travel time. Finally, the travelers compare the updated travel times of alternatives and choose, among them, the best one from their point of view. The proposed model has been applied to a test network where two different information sources have been considered. Results highlight the effectiveness of the model in quantifying and simulating drivers' compliance with information.
In the current research, a smart grid is considered as a network of distributed interacting nodes represented by renewable energy sources, storage and loads. The source nodes connect or disconnect in a stochastic mann...
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In the current research, a smart grid is considered as a network of distributed interacting nodes represented by renewable energy sources, storage and loads. The source nodes connect or disconnect in a stochastic manner due to the intermittent nature of natural resources such as wind and solar irradiance. Prediction and stochastic modelling of electrical energy flow is a critical task in such a network to achieve load levelling and/or peak shaving in order to minimise the fluctuation between off peak and peak energy demand. The behaviour of source nodes in this grid is modelled and administered through a scheduling strategy control algorithm using the historical data collected from the system. The stochastic model predicts future power consumption/injection to determine the power required for storage components. The proposed stochastic model based on Box-Jenkins method satisfies two major objectives. It predicts the most efficient state of electrical energy flow between a distribution network and nodes as well as minimising the peak demand and off peak consumption of deriving electrical energy from the main grid. MATLAB/Simulink is deployed to simulate the platform. The performance of the models is validated against autoregressive moving average (ARIMA) and Markov Chain models. The results demonstrate that the proposed method outperforms both ARIMA and Markov Chain model. Results are presented, the strengths and limitations of the approach are discussed, and possible future work is described.
A smart ASIC chip was previously designed, fabricated and tested for monitoring of volatile organic compounds (VOC), with both signal processing electronics and resistive sensors integrated within a single CMOS device...
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ISBN:
(纸本)9781479978014
A smart ASIC chip was previously designed, fabricated and tested for monitoring of volatile organic compounds (VOC), with both signal processing electronics and resistive sensors integrated within a single CMOS device. The ASIC has been successfully tested using different types of sensitive materials, including carbon black-polymer composites and bi-functional linker molecules with gold nanoparticles. Different geometries and configurations have been designed for each generation of the device. In the interest of getting a better understanding of the sensor behaviour, which is affected by a number of physical phenomena, namely temperature, humidity, chemical properties of the sensing materials, and geometry of the electrodes, among others, a novel multiphysics model of the device has been developed and simulation results are reported in this paper. The model explores coupled electrical and thermal behaviour of the resistive microsensors obtained after depositing sensing materials upon the electrodes built in the second metal layer of a CMOS process. The results show the distribution of electric potential and the distribution of temperature obtained for a set of resistive sensors made out of carbon black-polymer composites.
The mechanical behaviour of a superplastic material is often modelled by the power law relationship between the equivalent flow stress, the equivalent strain and the equivalent strain-rate at least over a limited rang...
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ISBN:
(纸本)9783038351801
The mechanical behaviour of a superplastic material is often modelled by the power law relationship between the equivalent flow stress, the equivalent strain and the equivalent strain-rate at least over a limited range of strain rates. This paper introduces an original mathematicalmodelling to determine the superplastic material constants m, n and K by means of experimental tests carried out using a standard forming die geometry.
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