the footwear manufacturing industry is a so-called "3D industry" (i.e., an industry that is dirty, dangerous, and difficult) because its processes involve the use of toxic substances. Moreover, this industry...
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ISBN:
(纸本)9781665436847
the footwear manufacturing industry is a so-called "3D industry" (i.e., an industry that is dirty, dangerous, and difficult) because its processes involve the use of toxic substances. Moreover, this industry is labor-intensive. Leading footwear brands that have attempted to replace labor with automated machinery have encountered problems such as a high defect rate and complicated manufacturing process, which reduce their production yield. the fundamental reasons for these problems are that the footwear industry manufactures products with different styles, materials, and sizes and must cope with challenges such as poor precision in processing tools, substantial variations in stitched shoe uppers, and soft and easily deformed sole materials. therefore, working trajectories must be generated for each pair of shoes before the automatic manufacturing process can commence. Consequently, trajectory recognition is essential for introducing automation into the footwear industry. Considering the aforementioned problems, this paper proposes a three-dimensional trajectory recognition technology, which involves three-dimensional point cloud model matching, for the junction trace of shoe parts. When the proposed technology is used, models are constructed for the upper and sole so that after they are joined, three-dimensional point cloud model matching can be conducted to determine the possible location of the junction trace according to the location of the sole in the assembly. Subsequently, a material identification device is used to examine the materials in the identified junction area and determine whether these materials are the same. the trajectory recognition operation for automated shoe production is completed by scanning the entire junction area where the upper and sole meet. the aforementioned method effectively resolves the drawbacks of existing automationmethods in the footwear industry, including the effects of the workpiece material and color on the accuracy of traj
Activities of daily living such as drinking and eating can be severely impaired for patients suffering from neurodegenerative diseases. One promising solution are assistive devices that apply corrective forces while s...
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ISBN:
(数字)9798350386523
ISBN:
(纸本)9798350386530
Activities of daily living such as drinking and eating can be severely impaired for patients suffering from neurodegenerative diseases. One promising solution are assistive devices that apply corrective forces while still allowing the intended movements. However, real-time estimation of the required forces requires a detailed understanding of the limb's impedance characteristics. Here, we test and validate the stiffness response of a computationally efficient neuro-musculoskeletal arm model and its response to various force perturbations. We demonstrate that the arm model predicts stiffness characteristics that closely match experimental data recorded from humans and presents real-time applicability, allowing for implementation in practical scenarios and. Additionally, we predict the stiffness response for novel force levels and arm configurations. In the future, these predictions could be used to estimate corrective forces for assistive devices in real-time.
Accurate modeling of complex dynamic environments is a fundamental requirement in robotics and automotive applications. While grid-mapping approaches used to be limited to static settings, methods for dynamic occupanc...
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ISBN:
(纸本)9781665476881
Accurate modeling of complex dynamic environments is a fundamental requirement in robotics and automotive applications. While grid-mapping approaches used to be limited to static settings, methods for dynamic occupancy grids have recently been developed, tracking spatial occupancy at a sub-object level, in every cell. In this paper, we present a generic dynamic occupancy grid tracker, which filters cell states and infers dynamics of the scene through the interaction of a grid-based and a particle-based model. these are set to represent different parts of the scene, and optimize particle allocation only to relevant areas, their predictions being fused accordingly. New hidden variables in the filtering process permit to address previously mishandled situations, like concurrent state predictions or specific filtering sensitivity. the presented method has been implemented, optimized on a GPU and tested on real-road conditions, embedded on an experimental vehicle.
Industry 4.0 vision is related to flexible and reconfigurable production systems with a special focus on robotic systems. Accuracy of robots together with decreased time needed for robot calibration are the key succes...
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ISBN:
(纸本)9781728189567
Industry 4.0 vision is related to flexible and reconfigurable production systems with a special focus on robotic systems. Accuracy of robots together with decreased time needed for robot calibration are the key success factors for robotic production systems. this paper reflects lessons learned from calibrating robot tools (such as grippers) and local coordinate systems (such as warehouse plates or shuttle plates) in industrial setting. We propose a new method for robot tool and workplace calibration with an absolute tracking system, in our case produced by Leica. Compared to the traditional manual approach relying on moving the robot arm to specific positions that are considered relatively to other objects, the proposed absolute approach is faster and more precise. It is contact-less compared to the currently used methods and thus it reduces risks of damages by accidental collisions. On the other hand, it requires costly equipment that is not frequent on production sites. the proposed approach is demonstrated on the Industry 4.0 Testbed use-case, hosted at the Czech Technical University in Prague. Withthis approach, we are able to make the robot calibration faster and more precise.
Smart transportation is an important part of building a smart city, and accurate traffic forecasting is crucial for citizen travel and urban construction. Aiming at the temporal and spatial dimensions in traffic forec...
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Smart transportation is an important part of building a smart city, and accurate traffic forecasting is crucial for citizen travel and urban construction. Aiming at the temporal and spatial dimensions in traffic forecasting, we focus on the extraction methods of the correlation between the two dimensions, and propose a new prediction model of the spatio-temporal graph attention network from the temporal correlation and the spatial correlation. the structure of the model is studied and analyzed. Finally, experiments are carried out on the mainstream traffic data sets, and by comparing with other prediction models, it is concluded that the evaluation indicators of the prediction model are better than other models.
Solving partial differential equations (PDEs) with random input parameters via standard numerical schemes such as finite element methods is computationally expensive, especially when high-dimensional random parameters...
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ISBN:
(纸本)9781665476881
Solving partial differential equations (PDEs) with random input parameters via standard numerical schemes such as finite element methods is computationally expensive, especially when high-dimensional random parameters are involved. Evaluation of the failure probability involves massive repeated solving equations, which would be computationally prohibitive via traditional Monte Carlo methods. Using neural networks as a surrogate model can somewhat alleviate computational complexity. However, constructing a relatively accurate neural network requires a substantial number of labeled data for training. In this paper, we propose a new mixed residual hybrid (MRH) method for failure probability estimation. On the benefits of absorbing equation form into the loss function of neural networks, none of the labeled data is needed in the training phase. Expensive numerical methods shall not be used unless to correct the outputs in suspicious intervals. Compared to the traditional Monte Carlo method requiring millions of computations, numerical experiments demonstrated the efficiency of the MRH method, which only requires a few thousand calculations.
Touchless technologies have gained significant popularity, particularly amidst the COVID-19 pandemic, as they addressed concerns related to germ transmission and hygiene during human-device interactions. this study ai...
Touchless technologies have gained significant popularity, particularly amidst the COVID-19 pandemic, as they addressed concerns related to germ transmission and hygiene during human-device interactions. this study aimed to develop an intuitive and user-friendly touchless system by combining eye gaze and hand gesture methods. Four regression machine learning models, namely Ridge regression, Lasso regression, Linear regression, and Gradient-boosting regressor, were trained and tested using standard metrics such as coefficient of determination (R2), mean absolute error (MAE), and mean squared error (MSE). the results indicated that Ridge regression outperformed the other models, demonstrating a high R2 value of 0.98. Leveraging this model, a simulation was conducted to evaluate the effectiveness of integrating eye gaze and hand gestures in realtime touchless interactions. the simulation demonstrated the successful integration of these modalities in the item selection process, providing users with a seamless and intuitive interaction method. this touchless interaction technology enabled effortless and accurate navigation of screens and facilitated item selections. the promising results highlighted the potential of this technology, presenting exciting opportunities for its integration with actuators. By incorporating actuators, touchless interaction systems could revolutionize various industries, including retail, healthcare, hospitality, and smart home automation.
Information exchange across different departments in factories must be structured and verified for effective production processes. However, any such exchange across networks to clients must be compliant to company sta...
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ISBN:
(纸本)9781728189567
Information exchange across different departments in factories must be structured and verified for effective production processes. However, any such exchange across networks to clients must be compliant to company standards so that uniformity and security in data dispensation is maintained. Open Platform Communications Unified Architecture (OPC UA) solutions provide users withthe flexibility of discharging information through network based protocols. this paper aims to build a compliance testing methodology for external vendors of an organisation who are interconnected withthe OPC UA Server-Client Protocols. the structure is built on a host of UA clients that test UA specifications and information models from these vendors. this enables an organisational entity, for example, a manufacturer, to provide its clients, in this case external vendors such as suppliers, withthe flexibility of conforming to prescribed standards in a testing phase on an automated digital platform rather than with older methods such as data transfer though databases or documents. An implementation of this approach is presented using example servers created for this purpose. It follows that external vendors can perform compliance testing and possibly improve their standards to match the company standards through remote testing after proper authentication measures provided by OPC UA.
One of the limitations in the development of really soft robotic devices is the development of soft actuators. In recent years, our research group has developed a new flexible shape memory alloy actuator that provides...
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One of the limitations in the development of really soft robotic devices is the development of soft actuators. In recent years, our research group has developed a new flexible shape memory alloy actuator that provides more freedom of movements and a better integration in wearable robots, especially in soft wearable robots. Shape memory alloy wires present characteristics such as force/weight ratio, low weight, and noiseless actuation, which make them an ideal choice in these types of applications. However, the control strategy must take into account its complex dynamics due to thermal phase transformation. Different control approaches based on complex non-linear models and other model-free control methods have been tested on real systems. Some exoskeleton prototypes have been developed, which demonstrate the utility of this actuator and the advantages offered by these flexible actuators to improve the comfort and adaptability of exoskeletons.
Withthe rising implementation of Home Energy Management Systems (HEMS), active studies had been done relative to power monitoring alternatives. Load monitoring is an essential block of HEMS;therefore, the improvement...
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