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Computing and Information Technology (ICCIT-1441), 2020 International Conference on

作者： Prithi Samuel Rajesh Kumar Dhanaraj Balamurugan Balusamy Narmatha C Department of Computational Intelligence SRM Institute of Science and Technology Chennai India Symbiosis Institute of Computer Studies and Research (SICSR) Symbiosis International (Deemed University) Pune India Associate Dean- Students Shiv Nadar University Noida India Industrial Innovation & Robotics Center Faculty of Computers and Information Technology University of Tabuk Tabuk City Kingdom of Saudi Arabia

For visually impaired, deaf-blind people, both communication and navigation are difficult activities and indoor navigation is becoming increasingly harder for them. It is even more difficult for deaf-blind people than it is for non-visually impaired people. People with visual impairments or deaf- blindness frequently rely on external support systems to make judgments, such as trained canines, humans, or specialized equipment. As a result, deaf-blind people are in desperate need of an assistive application that allows blind people to navigate and communicate freely without relying on others. The goal of the application is to create a more adaptable and cost-effective system for deaf-blind and visually impaired people. Through both outdoor and interior applications, as well as walking in even unfamiliar locations without relying on others.

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Creating Own AI Datasets from Different Language Sources Efficiently: Advantages, Disadvantages and Best Pracitces to Make Own Datasets

Creating Own AI Datasets from Different Language Sources Eff...

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International IEEE Conference and Workshop: Óbuda on Electrical and Power Engineering (CANDO-EPE)

作者： György Molnár József Cserkó Enikő Nagy Zoltán Balogh Kandó Kálmán Faculty of Electrical Engineering Óbuda University Budapest Hungary János Csere Apáczai Faculty Széchenyi University Győr Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemét Hungary Széchenyi University Doctoral School of Multidisciplinary Engineering Sciences (MMTDI) Győr Hungary Antal Bejczy Center for Intelligent Robotics John von Neumann Faculty Institute of Cyberphysical Systems Óbuda University Budapest Hungary Department of Informatics Faculty of Natural Sciences and Informatics Constantine the Philosopher University in Nitra Nitra Slovakia

Artificial Intelligence (AI) has become a ubiquitous technology that has the potential to revolutionize many industries. However, AI requires access to vast amounts of data to achieve its full potential. By understanding these data sources and the best practices for working with them, we can unlock the full potential of AI and create groundbreaking solutions that benefit society as a whole. Data sources can be utilized to train AI algorithms, including structured and unstructured data, but finding relevant datasets is challenging. The main problem is the international sources. Most of the datasets are available only in English or other common languages. However these are good sources, but translating them is expensive and time-consuming. This paper shows how to generate own datasets from open-source data with translation.

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Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology 2022年第4期60卷 589-590页

作者： F van den Noort C Manzini C H van der Vaart M A J van Limbeek C H Slump A T M Grob Robotics and Mechatronics Faculty of Electrical Engineering Mathematics and Computer Science Technical Medical Centre University of Twente Enschede The Netherlands. Department of Obstetrics and Gynecology University Medical Centre Utrecht Utrecht The Netherlands. Dynamics of Complex Fluids Max Planck Institute for Dynamics and Self-Organization Göttingen Germany. Multi-Modality Medical Imaging Faculty of Science and Technology Technical Medical Centre University of Twente Enschede The Netherlands.

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Correction to: Development of a dedicated 3D printed myocardial perfusion phantom: proof-of-concept in dynamic SPECT

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Medical & biological engineering & computing 2022年第6期60卷 1551-1553页

作者： Marije E Kamphuis Gijs J de Vries Henny Kuipers Marloes Saaltink Jacqueline Verschoor Marcel J W Greuter Riemer H J A Slart Cornelis H Slump Multi-Modality Medical Imaging (M3i) Group Faculty of Science and Technology Technical Medical Centre 2386 University of Twente P.O. Box 217 7500 AE Enschede The Netherlands. kamphuis@utwente.nl. Robotics and Mechatronics (RaM) Group Faculty of Electrical Engineering Mathematics and Computer Science Technical Medical Centre University of Twente Enschede The Netherlands. kamphuis@utwente.nl. Robotics and Mechatronics (RaM) Group Faculty of Electrical Engineering Mathematics and Computer Science Technical Medical Centre University of Twente Enschede The Netherlands. Department of Nuclear Medicine Ziekenhuis Groep Twente Hengelo The Netherlands. Medical Imaging Centre Department of Nuclear Medicine and Molecular Imaging University Medical Center Groningen University of Groningen Groningen The Netherlands. Biomedical Photonic Imaging Group Faculty of Science and Technology Technical Medical Centre University of Twente Enschede The Netherlands.

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Drone-Based Predictive Structure Analysis: A Review

Drone-Based Predictive Structure Analysis: A Review

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Sustainable Emerging Innovations in Engineering and Technology (ICSEIET), International Conference on

作者： Trushant Patil Durgesh Nandan Kanhaiya Sharma Deepak Parashar Department of Robotics and Automation SIT Symbiosis International (Deemed University) Pune India Department of Electronics and Telecommunication Engg. SIT Symbiosis International (Deemed University) Pune India Department of Computer Science & Engineering SIT Symbiosis International (Deemed University) Pune India Faculty of Engineering Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune India

Drone-based predictive structure analysis is a rapidly growing field that has the potential to revolutionize infrastructure and building inspection. In this review of the research, we give a general overview of how drones could increase the effectiveness and precision of structural analysis, particularly for keeping an eye on difficult-to-reach locations. The usage of drones for 3D mapping, inspection, and monitoring of diverse constructions, such as concrete buildings, bridges, tunnels, and dams. The investigations show that drone-based inspection can produce 3D models and high-resolution photos, allowing for remote monitoring and the early identification of possible problems. The findings show that drones may greatly boost infrastructure management's safety and effectiveness, making them an important tool for predictive structural research.

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Placing by Touching: An empirical study on the importance of tactile sensing for precise object placing

arXiv

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arXiv 2022年

作者： Lach, Luca Funk, Niklas Haschke, Robert Lemaignan, Séverin Ritter, Helge Joachim Peters, Jan Chalvatzaki, Georgia Neuroinformatics Group Technical Faculty Bielefeld University Germany Institut de Robòtica i Informàtica Industrial CSIC-UPC Spain Computer Science Department Technical University Darmstadt Germany PAL Robotics Research Department: Systems AI for Robot Learning Germany Hessian.AI Centre for Cognitive Science

This work deals with a practical everyday problem: stable object placement on flat surfaces starting from unknown initial poses. Common object-placing approaches require either complete scene specifications or extrinsic sensor measurements, e.g., cameras, that occasionally suffer from occlusions. We propose a novel approach for stable object placing that combines tactile feedback and proprioceptive sensing. We devise a neural architecture that estimates a rotation matrix, resulting in a corrective gripper movement that aligns the object with the placing surface for the subsequent object manipulation. We compare models with different sensing modalities, such as force-torque and an external motion capture system, in real-world object placing tasks with different objects. The experimental evaluation of our placing policies with a set of unseen everyday objects reveals significant generalization of our proposed pipeline, suggesting that tactile sensing plays a vital role in the intrinsic understanding of robotic dexterous object manipulation. Code, models, and supplementary videos are available on https://***/ view/placing-by-touching. Copyright © 2022, The Authors. All rights reserved.

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Multistable Energy Shaping of Passive Linear Systems with Hybrid Mode Selector

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IFAC-PapersOnLine 2020年第2期53卷 9118-9124页

作者： Stefano Massaroli Federico Califano Angela Faragasso Atsushi Yamashita Hajime Asama Department of Precision Engineering The University of Tokyo Faculty of Electrical Engineering Mathematics & Computer Science Robotics and Mechatronics University of Twente

This paper presents a novel control strategy for stable linear time–invariant systems operating with a finite number of set points. Inspired by the theory of passivity-based control, the proposed method aims at simultaneously and asymptotically stabilize all the desired working modes by means of a static nonlinear state feedback law. An asynchronous external signal is then employed to trigger a hybrid controller in order to switch between the different working modes. The proposed approach is validated by means of simulations performed on the ubiquitous mass-spring-damper system.

关键词： linear systems nonlinear control port–Hamiltonian systems hybrid systems multistability passivity–based control

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Application of Machine Learning to Performance Assessment for a class of PID-based Control Systems

arXiv

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arXiv 2021年

作者： Grelewicz, Patryk Khuat, Thanh Tung Czeczot, Jacek Nowak, Pawel Klopot, Tomasz Gabrys, Bogdan Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Department of Automatic Control and Robotics Gliwice44100 Poland University of Technology Sydney Faculty of Engineering and IT Advanced Analytics Institute NSW2007 Australia

In this paper, a novel machine learning derived control performance assessment (CPA) classification system is proposed. It is dedicated for a wide class of PID-based control industrial loops with processes exhibiting dynamical properties close to second order plus delay time (SOPDT). The proposed concept is very general and easy to configure to distinguish between acceptable and poor closed loop performance. This approach allows for determining the best (but also robust and practically achievable) closed loop performance based on very popular and intuitive closed loop quality factors. Training set can be automatically derived off-line using a number of different, diverse control performance indices (CPIs) used as discriminative features of the assessed control system. The proposed extended set of CPIs is discussed with comprehensive performance assessment of different machine learning based classification methods and practical application of the suggested solution. As a result, a general-purpose CPA system is derived that can be immediately applied in practice without any preliminary or additional learning stage during normal closed loop operation. It is verified by practical application to assess the control system for a laboratory heat exchange and distribution *** Codes 93 © 2021, CC BY-NC-SA.

关键词： Three term control systems

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Partially calibrated semi-generalized pose from hybrid point correspondences

arXiv

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arXiv 2022年

作者： Bhayani, Snehal Larsson, Viktor Sattler, Torsten Heikkilä, Janne Kukelova, Zuzana Center for Machine Vision and Signal Analysis University of Oulu Finland Czech Institute of Informatics Robotics and Cybernetics Czech Technical University Prague Czech Republic Computer Vision and Geometry Group Department of Computer Science ETH Zürich Switzerland Visual Recognition Group Faculty of Electrical Engineering Czech Technical University Prague Czech Republic

In this paper we study the problem of estimating the semi-generalized pose of a partially calibrated camera, i.e., the pose of a perspective camera with unknown focal length w.r.t. a generalized camera, from a hybrid set of 2D-2D and 2D-3D point correspondences. We study all possible camera configurations within the generalized camera system. To derive practical solvers to previously unsolved challenging configurations, we test different parameterizations as well as different solving strategies based on state-of-the-art methods for generating efficient polynomial solvers. We evaluate the three most promising solvers, i.e., the H51f solver with five 2D-2D correspondences and one 2D-3D correspondence viewed by the same camera inside generalized camera, the H32f solver with three 2D-2D and two 2D-3D correspondences, and the H13f solver with one 2D-2D and three 2D-3D correspondences, on synthetic and real data. We show that in the presence of noise in the 3D points these solvers provide better estimates than the corresponding absolute pose solvers. Copyright © 2022, The Authors. All rights reserved.

关键词： Cameras

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Electric Vehicle Charging Demand Prediction using Multiresolution Sinusoidal Neural Network Optimized with Addax Optimization

Electric Vehicle Charging Demand Prediction using Multiresol...

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Trends in Material science and Inventive Materials (ICTMIM), International Conference on

作者： Rajesh Munirathnam Rohit P. Jadhav Nilesh M. Mahajan Amit Barve M. E. Shashi Kumar Natrayan L Data & Analytics Division TechnoGen Inc Hillsborough New Jersey USA Department of Robotics and Automation D.Y. Patil College of Engineering Akurdi Pune Maharashtra Department of Computer Science and Engineering Parul Institute of Technology Faculty of Engineering and Technology Parul University Limda Gujarat Department of Mechanical Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru Karnataka Department of Mechanical Engineering Saveetha School of Engineering SIMATS Chennai Tamil Nadu

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

Electric Vehicle (EV) charging demand prediction, while essential for optimizing charging infrastructure and energy management, faces challenges such as data inaccuracies and uncertainties in user behavior patterns. These issues define inaccurate demand forecasts which cause the wrong placement of charging stations and distribution of energy. Also, as the pattern of the EV charging is not static may change due to many factors such as climate, time of day, price preference among others, the prediction models may not handle the dynamism and hence lower the reliability of the forecast results. To overcome these drawbacks, this manuscript proposes an efficient approach for EV charging demand prediction. The data is gathered from a dataset on EV charging. The data is then sent to pre-processing. Using the Maximum Correntropy Quaternion Kalman Filter (MCQKF), the pre-processing section eliminates missing values and normalizes the input. To forecast EV charging demand, the Multiresolution Sinusoidal Neural Network (MSNN) receives the results of the pre-processing data. MSNN’s weight parameter is optimized using Addax Optimization (AO). The proposed MSNN-AO is utilized within the MATLAB platform. The proposed MSNN-AO technique is compared with the existing techniques such as Long Short-Term Memory Neural Network (LSTMNN), Heterogeneous Spatial-Temporal Graph Convolutional Network (HSTGNN) and Artificial Neural Networks (ANN), respectively. The MSNN-AO method achieves an accuracy of 97%, precision of 95%, and a Root Mean Square Error (RMSE) of 2.2%, demonstrating its superior performance in predicting EV charging demand. This highlights the proposed method’s effectiveness in minimizing prediction errors, reducing RMSE by 22.36%, and improving precision by 14.89% compared to existing methods. The MSNN-AO method’s higher accuracy and precision, coupled with its robust performance, make it a reliable and efficient solution for EV charging demand forecasting.

关键词： Accuracy Uncertainty Quaternions Energy resolution Electric vehicle charging Reliability Kalman filters Spatial resolution Root mean square Optimization

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