Inline Inspection with an Industrial Robot (IIIR) for Mass-Customization Production Line

Wu, Zai-Gen; Lin, Chaoyi; Chang, Hao‐Wei; Lin, Po Ting

doi:10.3390/s20113008

Cited by 18 publications

(8 citation statements)

References 12 publications

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“…The first case used Multilateration based on wireless measurements with sensor numbers 1~3 as the second case used the sensor numbers 1~4. An AGV was desired to move from a starting point : [1,1] to an end point : [4,4], as shown as the blue straight line in Fig. 3…”

Section: A Navigation Along Linear Moving Trajectoriesmentioning

confidence: 99%

“…In the era of Industry 4.0, manufacturing has been moving on from industrial automations to massive needs of production customizations in smart factories. Intelligent robotics and vehicle systems have drawn great attentions and been applied for automatic customization productions [1]. One of the most attractive solutions to customized factory logistics was to use Autonomous Ground Vehicle (AGV) [2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

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Probabilistic Indoor Positioning and Navigation (PIPN) of Autonomous Ground Vehicle (AGV) Based on Wireless Measurements

2021

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Recently, Autonomous Ground Vehicles (AGV) and mobile robots have been rapidly developed in various engineering applications, such as Industry 4.0 factory and smart manufacturing. Indoor navigation was one of the most important tasks for the said mobile systems as they were often designed to move from one location to another location autonomously without contacting the surrounding objects along the moving path in a usually dynamic and complex indoor environment. There were two key steps to achieve Simultaneous Localization and Mapping (SLAM). First, indoor positioning of the mobile system based on some measurements was done. The second step was to navigate itself inside the indoor map. This was a very challenging problem because there always existed uncertainties in the measurements. It was desired to estimate the positioning errors and determine a safe moving path with high reliability. This paper presented the methodologies for wireless indoor positioning and navigation of AGV with measurement uncertainties. Two kinds of AGV moving trajectories with various design parameters were simulated: a linear trajectory and a curved one. It was found that both greater number of sensors being used for wireless measurements and greater number of measurement trials for Multilateration could effectively improve the accuracy of AGV positioning. INDEX TERMSAutonomous Ground Vehicle (AGV), Indoor Positioning and Navigation (IPN), Monte Carlo Simulations (MCS), Multilateration, Wireless Distance Measurement.

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Section: A Navigation Along Linear Moving Trajectoriesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Probabilistic Indoor Positioning and Navigation (PIPN) of Autonomous Ground Vehicle (AGV) Based on Wireless Measurements

2021

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“…UWB enables simultaneous real-time tracking of objects and provides their localisation despite indoor obstructions due to the advantage of working under non-line-of-sight (NLOS) conditions [21], [22]. UWB technology enables an efficient combination of accuracy, scalability and reliability, which are very crucial in the applications of indoor logistics, such as tracking people and assets, and controlling the automated guided vehicles (AGVs) [23], [24].…”

Section: Introductionmentioning

confidence: 99%

Precision Positioning for Smart Logistics Using Ultra-Wideband Technology-Based Indoor Navigation: A Review

et al. 2022

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Logistics is an important driver for the competitiveness of industries and material supply. The development of smart logistics, powered by precise positioning and communication technologies can significantly improve the efficiency of logistics. The emerging technology of ultra-wideband (UWB) precision positioning has attracted significant attention throughout the previous decade owing to its promising capabilities over other radio frequency-based indoor localisation systems. In addition, UWB is characterised by large bandwidth and data rate, short message length, low transmission power and high penetration capability, which are all favourable for indoor positioning applications. However, UWB localisation technology faces several challenges that are somewhat similar to other technologies, such as mitigating errors that originate from non-line-of-sight (NLOS) situations and tackling signal interference in dense environments, and when required to operate in extreme conditions. This paper reviews the most recent advances made in UWB positioning systems over the last five years, with a focus on high-ranking articles. In addition to going through more conventional solutions to UWB challenges, modern solutions, which involve the use of machine learning and sensor data fusion, are discussed. We highlight the most promising findings of the recently implemented and foreseen UWB positioning systems by providing a summary of each reviewed article. Additionally, we address a major challenge that faces the UWB positioning technology: NLOS situations, focusing on some proposed remedies such as multi-sensor fusion and machine learning. As an application, this study introduces how UWB technology promotes smart logistics by offering indoor positioning to improve efficiencies in the delivery of goods from the source to the customer. Furthermore, it demonstrates the benefits of UWB technology for accurate positioning and tracking of both stationary and moving items, and machinery in an indoor logistics environment.

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“…Due to the rapid development and wide implementation of advanced technologies, we are undergoing a revolution toward smart manufacturing, named Industry 4.0. Quick response to consumers' fast-shifting and individualized needs, is regarded as one of the core competitiveness for the success of the enterprises in many industry sectors [1][2][3]. In this context, as a hybrid production mode of made-to-measure and mass production, leveraging the personalized services and high productivity of the two modes, mass customization has been increasingly applied in the apparel industry recently [4,5].…”

Section: Introductionmentioning

confidence: 99%

Construction of Garment Pattern Design Knowledge Base Using Sensory Analysis, Ontology and Support Vector Regression Modeling

Wang¹,

Zeng²,

Tao³

et al. 2021

IJCIS

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Garment pattern design is an extremely significant factor for the success of fashion company in mass customization and industry 4.0. In this paper, we proposed a new approach for constructing a garment pattern design knowledge base (GPDKB) using sensory analysis, ontology and support vector regression (SVR) modeling, aiming at systematically formalizing the complete knowledge on garment pattern design and realizing garment pattern associated adaptation. This approach has been described and validated in the scenario of personalized men's shirt design. The GPDKB consists of three components: conceptual knowledge base, relationship knowledge base and adaptation rules knowledge base. After selecting the optimal garment patterns using data twins-driven technique, the GPDKB has been built by learning from quantitative relationships between garment structure lines, controlling points and garment patterns and then simulated for pattern parameters prediction and pattern associate adaptation. Finally, the performance of the presented approach was compared with other classical data learning techniques, i.e., multiple linear regression and backpropagation-artificial neural network. The experimental results show that SVR-based approach outperform another two techniques with the lowest average of mean squared errors (0.1279) and average of standard deviation (0.1651). And the adaptation effect of GPDKB is equivalent to existing grading method. The general principle of the proposed approach can be adapted to creation of design knowledge bases for other type garments such as compression leggings. In fashion industry, the proposed GPDKB can effectively support designers by rapidly, accurately and automatically predicting relevant pattern adaptation parameters during garment pattern design.

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Inline Inspection with an Industrial Robot (IIIR) for Mass-Customization Production Line

Cited by 18 publications

References 12 publications

Probabilistic Indoor Positioning and Navigation (PIPN) of Autonomous Ground Vehicle (AGV) Based on Wireless Measurements

Probabilistic Indoor Positioning and Navigation (PIPN) of Autonomous Ground Vehicle (AGV) Based on Wireless Measurements

Precision Positioning for Smart Logistics Using Ultra-Wideband Technology-Based Indoor Navigation: A Review

Construction of Garment Pattern Design Knowledge Base Using Sensory Analysis, Ontology and Support Vector Regression Modeling

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