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Design and Implementation of a QR-Enabled Autonomous Bartender Using a User-Friendly Interface

Design and Implementation of a QR-Enabled Autonomous Bartend...

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international conference on methods and models in automation and robotics (MMAR)

作者： Joseph El Chartouni Elio El Ghaoui Gaby Abou Haidar Roy Abi Zeid Daou Department of Mechatronics Engineering La Sagesse University Beyrouth Lebanon merican University of Science and Technology Faculty of Engineering Zahle Lebanon Department of Mechatronics and Biomedical Engineering La Sagesse University Beyrouth Lebanon

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

the QR-Enabled Autonomous Bartender system introduces a pioneering approach to revolutionize beverage service within the hospitality sector. the Makr Shakr is a notable example of robotic bartending systems, renowned for its sleek design and advanced automation capabilities. However, existing works in this domain are often characterized by their high cost and lack of customization options, making them inaccessible to many establishments. the objective of this paper is to present the design, construction, and implementation of a stationary robotic bartender system enabled with QR code interaction, highlighting its potential to enhance customer experience and operational efficiency in bars and restaurants. the proposed system objectives encompass the design and construction of a stationary robotic bartender, the development of a user-friendly mobile website, the implementation of a personalized ordering system, and the optimization of beverage mixing and dispensing efficiency. Utilizing chrome and wood construction, this system balances durability with cost-effectiveness. the implementation of this initiative promises to advance automation and QR technology in the food and beverage industry, offering valuable insights into robotics, automation, and web development while enhancing customer experience and operational efficiency in bars and restaurants. As for validation, the system underwent rigorous testing, with a total of 210 trials resulting in 35 trials for each drink over a period of approximately 7 hours. Impressively, the system demonstrated an overall accuracy of $96.1 \%$ with an average response time of 0.4 seconds.

关键词： automation Costs Accuracy Service robots QR codes Beverage industry Time factors

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Evidential versus Bayesian Estimation for Radar Map Building

Evidential versus Bayesian Estimation for Radar Map Building

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international conference on Control, automation, robotics and Vision (ICARCV)

作者： John Mullane Martin D. Adams Wijerupage Sardha Wijesoma School of Electrical & Electronic Engineering Nanyang Technological University Singapore

this paper discusses the role played by signal detection algorithms in the mobile robot map building problem. Typical mapping techniques make the assumption that the internal signal detection, which is required to produce an (r, rho) point estimate, is ideal. that is, the probability of detecting the signal is unity, and the probabilities of a false alarm or missed detection are zero. In the case of grid mapping, this allows for the occupancy probability to be distributed under the constraint of a unity summation amongst affected cells. In the case of SLAM, this allows for a feature's (x,y) coordinates to be modeled with (Gaussian) probability density functions. this paper shows that typical signal detection algorithms contain all the necessary measurement models to exactly calculate the map occupancy estimates. Furthermore, once restrictive signal assumptions are relaxed, its shown that evidence theory and not Bayesian theory should be used in the combination and updating of the map estimates. the ideas presented in this paper are demonstrated in the field robotics domain using a millimeter wave radar sensor. Target presence and absence beliefs are derived directly from signal likelihood ratios as opposed to a priori assigned constants as is typical for mapping algorithms. Results obtained from outdoor sensing experiments, show the improvement of this new model, given targets of fluctuating radar cross section (RCS)

关键词： Bayesian methods Signal detection Radar cross section Signal mapping Millimeter wave radar Mobile robots Radar detection Simultaneous localization and mapping Probability density function Robot sensing systems

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Interval type-2 non-singleton type-2 Takagi-Sugeno-Kang fuzzy logic systems using the hybrid learning mechanism recursive-least-square and back-propagation methods

Interval type-2 non-singleton type-2 Takagi-Sugeno-Kang fuzz...

引用

international conference on Control, automation, robotics and Vision (ICARCV)

作者： Gerardo M. Mendez Maria de los Angeles Hernandez Electrical and Electronics Engineering Department Instituto Tecnologico de Nuevo Leon-ITNL Nuevo Leon Mexico Business Administration Department Instituto Tecnologico de Nuevo Leon-ITNL Nuevo Leon Mexico

this article presents a novel learning methodology based on the hybrid mechanism for training an interval type-2 non-singleton type-2 Takagi-Sugeno-Kang fuzzy logic systems (FLS). Using input-output data pairs during the forward pass of the training and prediction processes, the interval type-2 non-singleton type-2 TSK FLS the consequent parameters were tuned by using the recursive least squares (RLS) method. In the backward pass, the antecedent parameters were tuned by using the back-propagation (BP) method. As reported in the literature, the performance indexes of these hybrid models have proved to be better than the individual training mechanism when used alone. the proposed hybrid methodology was tested thru the modeling and prediction of the steel strip temperature at the descaler box entry as rolled in an industrial hot strip mill. Results show that the proposed method compensates better for uncertain measurements than previous type-2 Takagi-Sugeno-Kang using non-hybrid or only back propagation learning mechanisms.

关键词： Training Temperature measurement Fuzzy systems Learning systems Fuzzy logic Strips Measurement uncertainty

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Warehouse automation solution through a goods-to-person AMR

Warehouse automation solution through a goods-to-person AMR

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international conference on methods and models in automation and robotics (MMAR)

作者： Dimitra Zotou Stefanos Papadam Christina theodoridou Andreas Kargakos Kosmas Tsiakas Dimitrios Alexiou Ioannis Kostavelis Dimitrios Giakoumis Nikolaos Morenos Dimosthenis Ioannidis Dimitrios Tzovaras Centre for Research and Technology Hellas Information Technologies Institute (CERTH / ITI) Thessaloniki Greece Department of Supply Chain Management International Hellenic University Katerini Greece TETTIX - N.MORENOS SINGLE MEMBER PC Thessaloniki Greece

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

the use of goods-to-person robotic systems in a warehouse enhances storage density by devoting specific areas for Automated Mobile Robots (AMRs). Nevertheless, operation in narrow aisles and confined spaces presents notable challenges. this study outlines a comprehensive approach for AMRs to autonomously navigate within narrow aisles of a warehouse, ensuring safety and streamlining order completion. the goal is to independently collect and transport bins with products referred to the order, to the workstation area, where workers finalize order packing. Precise positioning of fiducial markers on the floor, initiates a fusion-based localization system that merges information from wheel odometry and fiducial detection. the markers are organized as an undirected graph to facilitate navigation purposes and Dijkstra algorithm is employed to successfully generate both safe and optimal paths. A pipeline has been established for the retrieval and positioning of bins from shelves or workstations to optimize the order picking process. the proposed method has been tested on a simulation environment with realistic constraints stem from the development of an autonomous warehouse environment.

关键词： Location awareness automation Navigation Pipelines Wheels Workstations Safety

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Drive Modeling and Dynamic Control in Mössbauer Spectroscopy for Space & Terrestrial Applications

Drive Modeling and Dynamic Control in Mössbauer Spectroscop...

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international conference on methods and models in automation and robotics (MMAR)

作者： Mohammad Beyki Justus Pawlak Martin Mutz Robert Patzke Franz Renz Department of Computer Engineering and Applied Mathematics University of Applied Sciences and Arts Hannover Germany Department of Integrated Circuits and Embedded Systems University of Applied Sciences and Arts Hannover Germany Institute of Inorganic Chemistry Leibniz University Hannover Germany

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

An important component of the Mössbauer spectrometer is the Mössbauer drive, which allows, utilizing the Doppler effect, to vary the amount of energy of the emitted gamma quanta so that it corresponds to the resonance energy and energetically excites the irradiated nuclei. this paper deals with drive modelling and control in Mössbauer spectroscopy. the equations of motion of the linear drive are derived and compared in different versions. In this context, the single-mass representation proves to be a sufficiently accurate model, which shows almost identical results compared to multibody models. this leads to a reduction of the system order from n=6 to n=2, which greatly simplifies the evaluation steps in this context and the further controller design modalities. Based on this, a heuristic control concept is developed that fundamentally revises common design approaches and opens up a broad spectrum of research. the controller design provides for a combination of signal-smoothing and signal amplifying low-pass filtering in combination with dynamic input vector normalisation. this achieves the desired frequency and amplitude response of $1.1485 \cdot 10^{3} \frac{\mathrm{rad}}{\mathrm{s}}$ and 0.3 mm and optimises the dynamics for real laboratory use.

关键词： Spectroscopy automation Filtering Aerospace electronics Mathematical models Vectors Resonance

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Model Identification and Path Following for an Inland Vessel Using IENC Data

Model Identification and Path Following for an Inland Vessel...

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international conference on Control, automation, robotics and Vision (ICARCV)

作者： M. AmirReza Haqshenas Jan Swevers Peter Slaets Research and Development PERISKAL Wuustwezel Belgium Department of Mechanical Engineering KU Leuven Celestijnenlaan 300 Heverlee Belgium Department of Mechanical Engineering and Flanders Make@KU Leuven MECO Research Team Celestijnenlaan 300 Heverlee Belgium

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

this paper presents a model and parameter estimation methods for an inland cargo catamaran. this model is used in an NMPC scheme to address the path following problem of the vessel in inland waterways. this NMPC scheme derives the control action by minimizing a cost function while meeting constraints. the path consists of waypoints that define safety contours that are derived from IENC. In Addition, circular geometries are used to define safety contours around obstacles along the fairway. the model and NMPC are validated through simulation of a section of Leuven canal.

关键词： Geometry Irrigation Parameter estimation automation Navigation Cost function Data models Safety Robots

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Generating an industrial process graph from 3D pipe routing information

Generating an industrial process graph from 3D pipe routing ...

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international conference on Emerging Technologies and Factory automation (ETFA)

作者： Seppo Sierla Mohammad Azangoo Valeriy Vyatkin Department of Electrical Engineering and Automation Aalto University Espoo Finland Department of Computer Science Luleå University of Technology Luleå Sweden

ISBN: (数字)9781728189567

ISBN: (纸本)9781728189574

the automatic generation of digital twins of industrial processes requires the integration of several sources of information. If the twin is expected to accurately capture thermo-hydraulic phenomena, dimensions of tanks and other process components as well as detailed pipe routing information is relevant. Such information is not comprehensively captured in P&IDs (Piping & Instrumentation Diagrams), but it is available from 3D CAD models. However, information about control loops is not available from 3D CAD models, but is available from P&IDs. Previous research has demonstrated the extraction of such information from machine-readable P&IDs and 3D CAD models and converting this information to graphs. Further research is expected on applying graph matching methods for integrating these separate graphs to a common graph-based data structure that captures all of the desired information. this common model could support further work to develop digital twins. A major obstacle to this is that the graphs that have currently been generated from P&IDs and 3D CAD models are at very different abstraction levels, so graph matching methods are not feasible. this article address this obstacle by building on previous work, in which graphs were generated from P&IDs and 3D CAD models. the contribution of this paper is several novel algorithms for preprocessing a 3D CAD generated graph, until it is at the same level of abstraction as a P&ID generated graph of the same industrial process. the algorithms are demonstrated in the context of a laboratory process.

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Proposal of an Automated Feature Engineering Pipeline for High-Dimensional In-Vehicle Bus Data Using Reinforcement Learning

Proposal of an Automated Feature Engineering Pipeline for Hi...

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robotics, automation and Artificial Intelligence (RAAI), IEEE international conference on

作者： Julian Mueller Jonas Wagenknecht Florian Schuchter Georg Frey Mercedes-Benz AG Sindelfingen Germany Reutlingen University Reutlingen Germany Chair of Automation and Energy Systems Saarland University Saarbrücken Germany

ISBN: (数字)9798331520038

ISBN: (纸本)9798331520045

the complexity of the communication between electronic control units in contemporary vehicles is increasing with the rising demand of customer functions such as automated driving and infotainment resulting in up to several thousand data elements (signals) per data bus. Consequently, engineers have no choice but to apply data science methods to extract meaningful insights from this high-dimensional communication data, particularly before training machine learning models. A critical step in this process is identifying the bus signals relevant for a specific data science task. Extracting them manually is not only time-consuming but it also demands a high degree of in-vehicle communication knowledge which is hard to obtain. To address this challenge, we propose an automated feature engineering approach that leverages reinforcement learning combined with state-of-the-art feature selection and engineering methods and a tunable sampling rate for the bus data. Due to the high degree of automation it requires little prior knowledge of how in-vehicle communication works. Our method enhances important key performance indicators for machine learning model quality for the task of energy consumption prognosis and significantly reduces the number of bus signals required for accurate model predictions. this approach does not only improve the understanding of relevant data but also reduces the model's size as less features are used for the prediction, leading to more efficient and interpretable machine learning solutions.

关键词： Training Energy consumption automation Pipelines Reinforcement learning Predictive models Data science Feature extraction Data models Robots

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Modeling Cerebro-Vascular Autoregulation after Postural Change Perturbations : Plenary Talk

Modeling Cerebro-Vascular Autoregulation after Postural Chan...

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international Symposium on Computational Intelligence and Informatics

作者： Andrea DeGaetano IRIB CNR

ISBN: (纸本)9798350398830

Mathematical models of the cardiovascular system and of cerebral autoregulation (CAR) have been employed for several years in order to describe the time course of pressures and flows changes subsequent to postural changes. the assessment of the degree of efficiency of cerebral auto regulation has indeed importance in the prognosis of such conditions as cerebro-vascular accidents or Alzheimer. In the quest for a simple but realistic mathematical description of cardiovascular control, which may be fitted onto non-invasive experimental observations after postural changes, the present work proposes a first version of an empirical Stochastic Delay Differential Equations (SDDEs) model. the model consists of a total of four SDDEs and two ancillary algebraic equations, incorporates four distinct delayed controls from the brain onto different components of the circulation, and is able to accurately capture the time course of mean arterial pressure and cerebral blood flow velocity signals, reproducing observed auto-correlated error around the expected drift.

关键词： Mechatronics Perturbation methods Stochastic processes Differential equations Brain modeling Mathematical models Regulation

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Research on methods of Pavement Distress Detection Based on Object Detection Convolutional Neural Network

Research on Methods of Pavement Distress Detection Based on ...

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robotics, Control and automation (ICRCA), international conference on

作者： Xingang Wang Yaxin Huang Yongjun Shao Chihang Zhao Youfeng Zheng Xinyi Ma Wenhao Deng Ziyi Zhang Shaanxi Expressway Engineering Testing and Testing Co. Ltd Xi'an P. R. China School of Transportation Southeast University Nanjing P. R. China

ISBN: (数字)9798350344721

ISBN: (纸本)9798350344738

Aiming at the problem that the accuracy of pavement distress detection is easily affected by complex texture, noisy background, uneven illumination conditions and external environmental interference of highway pavement distress images, this paper studies the methods of pavement distress detection based on object detection Convolutional Neural Network. Firstly, the methods of pavement distress detection based on Faster-RCNN, YOLO-V5s, and SSD are compared and analyzed. Secondly, three variants of CNN models are investigated for pavement distress detection, including FR-PDD, YOLO5s-PDD and SSD-PDD. Finally, the comparative experiments were conducted, and the results showed that the average of Yolov5s-PDD network is superior to the other two methods, with an average accuracy of 98.1%.

关键词： YOLO Road transportation Training Accuracy Lighting Interference Real-time systems

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