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9th International Conference on Movement and Computing, MOCO 2024 Beyond Control

作者： Dertien, Edwin Van Delden, Robby Reidsma, Dennis Robotics And Mechatronics University Of Twente Enschede Netherlands Human Media Interaction University Of Twente Enschede Netherlands

ISBN: (纸本)9798400709944

This paper discusses how improvisation theatre can be used as a tool for design and (design) education in the field of Human-Robot Interaction. This tool has been explored in settings focused on design education for students as well as care professionals. In this paper, a format and set of guiding principles that were found to work constructively will be presented, as well as a discussion on outcomes, results, and insights from a number of sessions. © 2024 Owner/Author.

关键词： Human robot interaction

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A Novel Solution to Transportation Safety 20

A Novel Solution to Transportation Safety

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20th IEEE International Conference on Smart Communities: Improving Quality of Life using AI, robotics and IoT, HONET 2023

作者： Rodriguez, Jorge Diaz Steele, Steven Ovando, Ammy Debnath, Gopi Tanveer, Muhammad Hassan Voicu, Razvan Cristian Kennesaw State University Department of Robotics & Mechatronics Engineering Atlanta United States

ISBN: (纸本)9798350331110

As the popularity of autonomous cars increases, a significant number of semi-autonomous vehicles have been sold, highlighting the technology's imperfections through associated crashes. These incidents can render motor vehicle operators in-capacitated, hindering their ability to request assistance. Consequently, the Intelligence Autonomous Monitoring (IAM) concept emerged. IAM is an intelligent monitoring system developed using a Raspberry Pi 4B, an Intel Real Sense D-455 camera, and the Convolutional Neural Network Yolov7, trained on car crash images. Convolutional Neural Networks have proven in-valuable for object detection, encompassing various applications, including identifying vehicles and individuals. This review aims to aid future researchers in enhancing the device's detection and prevention capabilities. © 2023 IEEE.

关键词： Convolutional neural networks

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AN IMPROVED AND ENHANCED DEPTH MAP APPROACH FOR OBSTACLE DETECTION IN UNKNOWN ENVIRONMENTS FOR REACTIVE AUTONOMOUS MOBILE ROBOTS

AN IMPROVED AND ENHANCED DEPTH MAP APPROACH FOR OBSTACLE DET...

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ASME 2024 International Mechanical Engineering Congress and Exposition, IMECE 2024

作者： Raju, Vomsheendhur Selekwa, Majura F. Mechatronics and Robotics Laboratory Department of Mechanical Engineering North Dakota State University FargoND United States

ISBN: (纸本)9780791888636

Interest in autonomous vehicles has attracted research into developing better navigation systems. Autonomous navigation systems guide unmanned vehicles to traverse any environment without human intervention;they require clear knowledge of the environment to make correct decisions. Information about the environment can be obtained from either ranging or vision sensors. Although ranging sensors such as LiDARs, radars, or sonars can detect the presence and location of obstacles, they don’t provide any information on whether the obstacles are traversable. On the other hand, vision sensors produce images similar to how human eyes perceive the environment, which can be processed to determine whether the sensed obstacle is traversable. Since vision sensors are light, less costly, and consume low power compared to LiDARs or Radars, there is an increasing interest in using them in autonomous navigation of unmanned ground vehicles. The main limitation of vision sensors for this purpose is their failure to directly identify the locations of the obstacles. Often, the location is determined by using a depth map, which is not always accurate and can be very computational. This paper proposes a new method of processing a depth map with improved accuracy. The depth of the closest objects to the stereo camera is extracted using the horizontal and vertical field of view of the sensor. It is further enhanced using morphological operations and the P-Tile segmentation technique to segment the obstacle(s) from its background and noise. This approach generates a denser map without any discontinuities, which leads to improved accuracy in locating close-by objects at less computational cost. Information from this depth map can be used as a low-cost alternative to ranging information in the navigation system for ground vehicles. Copyright © 2024 by ASME.

关键词： Stereo image processing

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ECG Disease Classification Using 1D CNN 2

ECG Disease Classification Using 1D CNN

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Dutta, Agniva Das, Manasi Iiest Shibpur School of Mechatronics and Robotics Kolkata India Dream Institute of Technology Ece Department Kolkata India

ISBN: (纸本)9798350360523

Recent improvements in the Artificial Intelligence and Machine Learning lead us to the automated models for detecting diseases based on ECGs. The previous models based on 2D CNNs had pretty good accuracy in ECG Classification, but these models requires us to create a 2D spatial representation from ECGs as ECGs are 1D temporal data. As these are typically done through CWT Scalogram it is computationally intensive. In this paper a model based on a 1D Convolutional Neural Network is proposed which can classify specific cardiac disease from ECG data. This model consists of four feature extracting Convolutional layers each succeeded by a Max Pooling layer and a dropout layer to prevent overfitting. This model is trained with ECGs of different types based on different cardiac disease like Cardiac Arrhythmia, Congestive Heart Failure and Normal Sinus Rhythm etc. and it can classify these diseases from ECGs. For training and evaluation MIT-BIH arrhythmia database have been used. It results in classification accuracy of 96.83% which is almost equal to the previous 2D CNN model with significant decrease in complexity. © 2024 IEEE.

关键词： Electrocardiograms

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Robust Cryptosystem Identification Under Various Operation Modes Using Deep Recurrent Neural Networks 4

Robust Cryptosystem Identification Under Various Operation M...

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4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Jeong, Ongee Martin, Antoinette Deborah Ahamadzadeh, Ezat Moon, Inkyu Department of Robotics and Mechatronics Engineering Daegu Korea Republic of Keimyung University Dongsan Hospital Daegu Korea Republic of

ISBN: (纸本)9798350360721

In the Ciphertext Only Attack (COA), an attacker can access and use only ciphertexts, identifying the type of cryptosystem is critical for further attack. The attacker can analyze patterns in the ciphertexts that have different forms according to the cryptosystem and recognize the type of cryptosystem. We propose deep learning-based cryptosystem identification by investigating eight cryptosystems, DES, S-DES, AES, S-AES, Blowfish, RC2, SPECK, and RSA. The Recurrent Neural Network (RNN)-based deep learning model with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) is utilized to identify cryptosystems. The proposed method is used to classify ciphertext in each operation mode such as CBC, CFB, OFB, and CTR, into the corresponding cipher system. The performance of the proposed method was evaluated with recall, precision, classification accuracy, and F1 score. To verify effectiveness and superiority, we compared the proposed method with different machine learning-based and deep learning-based classifiers such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and BERT, a Large Language Model (LLM). Moreover, the previous methods in cryptosystem identification were also compared with the proposed method, and the results showed that eight cryptosystems were successfully recognized under various operation modes. The proposed method outperformed the other machine learning-based, and its deep learning-based classifiers were superior in cryptosystem identification. Furthermore, the proposed method showed a classification accuracy of 97.3 and 96.2 % in CBC and CFB, respectively, while the highest accuracy in the previous methods was 20% in CBC and 85.5% in CFB. © 2024 IEEE.

关键词： Cryptography

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Behavior of cracked Euler–Bernoulli beam and inverse problem for assessing crack severity

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Noise and Vibration Worldwide 2022年第3期53卷 104-119页

作者： Samir Mohamed Mohamed Soliman, Ehab Mechatronics and Robotics Department Faculty of Engineering Egyptian Russian University Cairo Badr City Egypt

In this present study, natural frequencies of the first two modes of bending vibration for the cracked simply supported Euler–Bernoulli beam is determined using finite element analysis (FEA). FEA natural frequencies for the cracked beam are used to investigate the behavior of the cracked beam and also used in the inverse problem of crack depth detection. Dynamic behavior of the cracked simply supported beam is observed, and it is found that normalized mode shape at crack location has great effect on amount of decreasing of natural frequencies. When normalized mode shape at crack location is increased, then natural frequencies decrease. In this study, pattern of mode shape played a vital role in decreasing or increasing natural frequencies. At the midpoint of the beam, there is largest bending moment in first bending mode and there is nodal point in second bending mode. Harmonic analysis for the cracked simply supported beam is carried out to find von Mises stress responses and appearance of peaks at frequency of first bending mode is noticed in graphs of von Mises stress response, expressing high values of von Mises stress at crack tip. Inverse problem of assessing the crack depth is performed using results of FEA first mode frequency ratio and published experimental results and the method showed good results in case of high crack depth ratios. © The Author(s) 2021.

关键词： Natural frequencies

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Explicit Model Predictive Control Design based on Constrained Zonotope Propagation 7

Explicit Model Predictive Control Design based on Constraine...

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7th Scientific School: Dynamics of Complex Networks and their Applications, DCNA 2023

作者： Jnadi, Ali Khusainov, Ramil Nedelchev, Simeon Savin, Sergei Innopolis University Institute of Robotics and Computer Vision Innopolis Russia Innopolis University Center for Technologies in Robotics and Mechatronics Components Innopolis Russia

ISBN: (纸本)9798350305746

Zonotopes have become a widely used tool in control design, demonstrating their effectiveness in various applications ranging from state estimation to explicit model predictive control. However, the traditional use of zonotopes is limited by a set certain geometric shapes that restrict the range of state sets that can be considered. This paper proposes a novel approach to control design using constrained zonotopes that can encode arbitrary polytopes. We present a propagation scheme and an affine approximation of the exact control law for this representation, and discuss issues related to center identification for constrained zonotopes. A fast method for detecting set membership is also proposed based on lifting the constrained zonotopes into a higher dimensional space. The proposed method extends the range of shapes that can be considered in control design and offers a promising alternative to the limitations of regular zonotopes. It has the potential for wide-ranging impact in various areas of control, providing a valuable tool for solving complex control problems. © 2023 IEEE.

关键词： Convex optimization

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Mechanical Design Of Upper Limb Exoskeleton Intended To Be Used In A Human-Machine Interface 17

Mechanical Design Of Upper Limb Exoskeleton Intended To Be U...

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17th International Conference on Engineering of Modern Electric Systems, EMES 2023

作者： Roibu, Horatiu Bazavan, Lidia-Cristina Cismaru, Stefan-Irinel Resceanu, Ionut-Cristian Popescu, Dorin Bizdoaca, Nicu-George University of Craiova Faculty of Automation Computers and Electronics Mechatronics and Robotics Department Craiova Romania

ISBN: (纸本)9798350310634

An important aspect of robots' control highly depends on the type of interface which drives the interaction between humans and machines. In the present work, the authors propose a personal implementation of a control method for a mechanical structure using an exoskeleton interface. This work presents each stage of development, from concept design to implementation and testing. In the final part of the paper, the design and experiment results are shown, reflecting benefits and future improvement possibilities. © 2023 IEEE.

关键词： Exoskeleton (robotics)

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Vision Based Leader-Follower Control of Wheeled Mobile Robots using Reinforcement Learning and Deep Learning 9

Vision Based Leader-Follower Control of Wheeled Mobile Robot...

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9th International Symposium on System Security, Safety, and Reliability, ISSSR 2023

作者： Garmon, Kayleb Wang, Ying Kennesaw State University Department of Robotics and Mechatronics Engineering MariettaGA United States

ISBN: (纸本)9798350302479

Vision-based control of mobile robots often involves complex calculations to derive a control law. The reinforcement learning algorithm (Q-learning) offers a machine learning method to extrapolate a control law from an environment given discretized actions, without the need of complex calculations. In this paper, a vision-based controller is created using Q-Learning to enable tracking in a leader-follower configuration of two nonholonomic autonomous mobile robots. The follower robot gathers its desired trajectory values by using a deep learning SSD model to identify a distinguishing visual feature on the leader robot and uses a lidar to determine the distance between two robots. These parameters are utilized to select an optimal action of the follower robot through reinforcement learning. The emulated results in a ROS Gazebo environment show this method to be effective in enabling a wheeled mobile robot to follow another, while simultaneously avoiding obstacles. © 2023 IEEE.

关键词： Mobile robots

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EZ3micro - A Novel Miniaturized Pick & Place Prototype for Improved Industrial Applications 20

EZ3micro - A Novel Miniaturized Pick & Place Prototype for I...

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20th IEEE International Conference on Smart Communities: Improving Quality of Life using AI, robotics and IoT, HONET 2023

作者： Sangree, Haden Kofiah, Mahmoud Voicu, Razvan Cristian Tanveer, M. Hassan Kennesaw State University Department of Robotics & Mechatronics Engineering MariettaGA United States

ISBN: (纸本)9798350331110

This research paper focuses on the development of a miniaturized pick-and-place robotic prototype, which utilizes a magnetically levitated ACOPOS 6D shuttle developed by BandR Industrial Automation Corp. The aim is to meet the technological demands of various industries, including manufacturing, logistical, biomedical, and agricultural. The prototype boasts several cutting-edge features, such as wireless communication, battery-operated design, low weight, high stability, precision control, visual recognition, and advanced end effector control. The end effector can perform pick-and-place and orientation change functions, and the modular design allows for endless applications, including rapid sorting for manufacturing, agriculture, and logistics. Furthermore, the prototype offers advancements in biomedical applications by automating sample selection, transportation, and testing. Overall, this research paper presents a new technological advancement to help maintain the current growth rate of various industries. © 2023 IEEE.

关键词： Medical applications

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