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9th International Conference on Mathematics and computers in Sciences and Industry, MCSI 2024

作者： Muntean, Emanuel Leba, Monica University of Petrosani Department of System Control and Computer Engineering Petrosani Romania

ISBN: (纸本)9798350377224

This paper conducts a comparative analysis of human torso posture estimation methodologies, focusing on an inertial measurement unit (IMU) sensor coupled with an Arduino UNO as a wearable approach, and Kinect V2, utilizing OpenCV for posture analysis. The core objective of this study is to ascertain which method yields greater precision in the estimation of human torso posture. The IMU sensor, characterized by its wearability, provides the distinct advantage of unobtrusiveness and the capability to record motion across diverse environments. Conversely, Kinect V2 leverages computer vision techniques to derive posture estimations from visual data in real-time. Through comprehensive experimentation, this research evaluates the accuracy of both methodologies by juxtaposing their posture estimation outcomes. The findings of this investigation aim to significantly contribute to the enhancement of human posture estimation systems, with wide-ranging implications for health, sports, and ergonomics. © 2024 IEEE.

关键词： Ergonomics

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2D Posture Estimation of Human Arm 9

2D Posture Estimation of Human Arm

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9th International Conference on Mathematics and computers in Sciences and Industry, MCSI 2024

作者： Rosca, Sebastian Daniel Leba, Monica Sibisanu, Remus University of Petrosani Department of System Control and Computer Engineering Petrosani Romania

ISBN: (纸本)9798350377224

Human pose estimation and automatic detection is a common task in Human-computer Interaction but especially more capitalized in human-robot interaction inspired from biological form of human anatomy to realize a biomimetic control. In this sense, using human pose estimation it can be realized the whole human body posture estimation using anatomical human joints detection as inputs for specialized algorithms to calculate it based on key points obtained from a person Kinematic tree using regression, generation or part relation as models to estimate the optimal position from video or even from image. In this paper we propose a solution to estimate of 2D human arm posture of a subject using image capture as input for advanced machine learning algorithms to determine the subject joints position used to control in biomimetic manner a simulation of human like robotic arm with six degrees of freedom as a computer-aided model in Matlab-Simulink based on forward kinematics. © 2024 IEEE.

关键词： MATLAB

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Modeling and Simulation of Electric Vehicle Driveline 18

Modeling and Simulation of Electric Vehicle Driveline

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18th Iberian Conference on Information systems and Technologies, CISTI 2023

作者： Rus, Cosmin Leba, Monica Risteiu, Marius Nicolae Marcus, Razvan University of Petrosani UPET Department of System Control and Computer Engineering Petrosani Romania

ISBN: (纸本)9789893347928

Electric vehicle drivetrain modeling and simulation is a crucial aspect of electric vehicle design and development. A driveline is responsible for transferring power from the motor to the wheels, and the modeling and simulation process helps optimize the drivetrain design for efficiency, performance and safety. This paper presents in an extended manner the design and mathematical modeling of a dynamic transmission system of an electric vehicle. The mathematical model was simulated in Matlab Simulink and the obtained results were the basis of the implementation of the entire system in a small vehicle with offroad capabilities. This work is part of a larger project that has as its objective the creation of a complete electric vehicle starting from the design part and up to the testing on the roads. © 2023 ITMA.

关键词： Electric vehicles

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Quadruped Stanford Pupper Type Robot Modeling and Simulation 18

Quadruped Stanford Pupper Type Robot Modeling and Simulation

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18th Iberian Conference on Information systems and Technologies, CISTI 2023

作者： Mija, Nelu Leba, Monica Rus, Cosmin Muntean, Emanuel University of Petrosani UPET Department of System Control and Computer Engineering Petrosani Romania

ISBN: (纸本)9789893347928

Nowadays there are many research efforts in the field of artificial intelligence applied in all the fields of robotics. There are developed and trained new models both supervised and unsupervised learning. ln order to be able to get a reliable final product, a very important step is modeling and simulation. This paper focuses on the analysis of a quadruped robot, Stanford Pupper type, for which the mathematical model for the locomotor system was developed in order to be then implemented in a simulator that allows the development of machine learning algorithms for training it. There can be implemented in the simulator various use cases, like: learning to walk both supervised and unsupervised scenarios, learning to navigate on a zone with uneven surface and with small obstacles, or learning to climb stairs or other big obstacles. © 2023 ITMA.

关键词： Musculoskeletal system

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Architecture of AC-DC Energy Nodes in Supergrids: A Technical Foundation for Future Renewable Integration 5

Architecture of AC-DC Energy Nodes in Supergrids: A Technica...

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5th National and the 1st International Conference on Applied Research in Electrical Engineering, AREE 2025

作者： Mousavi, Mohammad Hossein Moradi, Hassan Rouzbehi, Kumars Razi University Department of Computer and Electrical Engineering Kermanshah Iran University of Seville Department of System Engineering and Automatic Control Seville Spain

ISBN: (纸本)9798350377170

The AC-DC Energy Nodes (ADENs) concept offers a transformative approach to modernizing power grids, particularly in the context of supergrids. By centralizing power flows from diverse renewable energy sources, such as offshore wind farms, ADENs enable efficient long-distance power transmission through HVDC technology. This design enhances the balance of supply and demand across regions and countries, significantly improving grid stability and resilience. However, the implementation of ADENs presents substantial technical, regulatory, and cybersecurity challenges. This study delves into these challenges while also addressing the geopolitical complexities of transnational connections, underscoring the critical importance of policy alignment for successful deployment. © 2025 IEEE.

关键词： Wind power integration

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On Approximate Opacity of Stochastic control systems

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IEEE Transactions on Automatic control 2024年第6期70卷 3846-3861页

作者： Liu, Siyuan Yin, Xiang Dimarogonas, Dimos V. Zamani, Majid Kth Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden Shanghai Jiao Tong University and Key Lab of System Control & Information Processing Ministry of Education Department of Automation Shanghai China University of Colorado Boulder Computer Science Department CO80309 United States Ludwig Maximilian University of Munich Computer Science Department Germany

This paper investigates an important class of information-flow security property called opacity for stochastic control systems. Opacity captures whether a system's secret behavior (a subset of the system's behavior that is considered to be critical) can be kept from outside observers. Existing works on opacity for control systems only provide a binary characterization of the system's security level by determining whether the system is opaque or not. In this work, we introduce a quantifiable measure of opacity that considers the likelihood of satisfying opacity for stochastic control systems modeled as general Markov decision processes (gMDPs). We also propose verification methods tailored to the new notions of opacity for finite gMDPs by using value iteration techniques. Then, a new notion called approximate opacity-preserving stochastic simulation relation is proposed, which captures the distance between two systems' behaviors in terms of preserving opacity. Based on this new system relation, we show that one can verify opacity for stochastic control systems using their abstractions (modeled as finite gMDPs). We also discuss how to construct such abstractions for a class of gMDPs under certain stability conditions. © 1963-2012 IEEE.

关键词： Stochastic control systems

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Human arm motion capture system 9

Human arm motion capture system

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9th International Conference on Mathematics and computers in Sciences and Industry, MCSI 2024

作者： Olar, Marius Leonard Leba, Monica Ionica, Andreea University of Petrosani Department of System Control and Computer Engineering Petrosani Romania University of Petrosani Department of Management and Industrial Engineering Petrosani Romania

ISBN: (纸本)9798350377224

The implementation of robotics and human support technologies has opened up new possibilities for recovering the mobility impaired and increasing human productivity in the last few decades. Exoskeletons have been developed as a major component of this progress in order to capture any form of arm motion be it passive or active. Motion capture systems, employing different sensors like IMU sensors, EMG sensors, motion sensors, fiber optic sensors are used to capture arm movements. These sensors provide information on position, movement, muscle contraction, and movement intent of the arm. The use of multiple sensor types allows for redundancy and accurate outcomes. Potentiometer position sensor can be combined with other types of sensors to measure acceleration, orientation, force exerted and arm bendability. The combinations improve accuracy and adaptability for arm motion capture during rehabilitation. Various combinations of adapted sensors can be used for each joint of the hand depending on the peculiarities of application. Sensors enable precise and natural control over recovery devices or exoskeletons which is especially important in terms of rehabilitation process improvement. © 2024 IEEE.

关键词： Exoskeleton (Robotics)

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CPL-SLAM: Centralized Collaborative Multi-Robot Visual-Inertial SLAM Using Point-and-Line Features

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IEEE Internet of Things Journal 2025年第12期12卷 21866-21875页

作者： Liu, Xin Wen, Shuhuan Liu, Huaping Richard Yu, F. Yanshan University Engineering Research Center The Ministry of Education for Intelligent Control System and Intelligent Equipment Key Lab of Intelligent Rehabilitation and Neuroregulation in Hebei Province Department of Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Tsinghua University Department of Computer Science and Technology Beijing100084 China Shenzhen University College of Computer Science and Software Engineering China Carleton University Canada

Traditional visual-inertial SLAM (Simultaneous Localization and Mapping) systems predominantly rely on feature point matching from a single robot to realize the robot pose estimation and environment map construction. However, in complex scenarios, these traditional systems struggle with issues such as tracking failures due to illumination changes, rapid movements, and low-texture environments, and they perform poorly in terms of mapping efficiency and global consistency. To address these challenges, we propose a centralized collaborative SLAM system that employs both point and line features for tracking in the robot and map fusion in the cloud. The proposed system leverages the fusion of point and line features across all instances in the process, which allows our method to achieve higher localization accuracy in structured, low-texture scenes. With the aid of classifying gravity-aligned vertical lines and spatial parallel lines, the proposed system can deliver faster and more accurate odometry in complex scenes. Furthermore, we developed intra-robot and inter-robot loop closure detection methods based on point and line features, generating a globally consistent sparse point cloud and structured scene map in the cloud. Our method is able to build richer maps while improving accuracy compared to existing methods. Experimental results on public datasets and in real-world environments show that, compared to existing advanced methods, our approach demonstrates better performance. © 2014 IEEE.

关键词： SLAM robotics

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Model-Based Optimization of Vaccination Strategies in Different Phases of Pandemic Virus Spread 18th

Model-Based Optimization of Vaccination Strategies in Diff...

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18th International Conference on Informatics in control, Automation and Robotics, ICINCO 2021

作者： Liu, Zonglin Omayrat, Muhammed Stursberg, Olaf Control and System Theory Department of Electrical Engineering and Computer Science University of Kassel Kassel Germany

ISBN: (纸本)9783031264733

This paper aims at applying optimal control principles to investigate optimal vaccination strategies in different phases of a pandemic. Background of the study is that many countries have started their vaccination procedures against the COVID-19 disease in the beginning of 2021, but supply shortages for the vaccines prevented that everyone could be vaccinated immediately. At the beginning of 2022, in contrast, the vaccine supply was ample, but the effectiveness of different existing vaccines to avoid infection by new virus variants was in doubt, as well as the acceptance of booster doses decreased over time. To account for these effects, two formulations of optimization tasks based on different epidemic models are proposed in this paper. The solution of these tasks determines optimal distribution strategies for available vaccines, and optimized vaccination schemes to reduce the need of booster doses for later phase. Effectiveness of these strategies compared with other popular strategies (as applied in practice) is demonstrated through a series of simulations © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Vaccines

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SSVEP Based BCI control of an Exoskeleton 18th

SSVEP Based BCI Control of an Exoskeleton

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18th International Conference on Interdisciplinarity in Engineering, INTER-ENG 2024

作者： Sibișanu, Remus Constantin Olar, Marius Leonard Roșca, Sebastian Daniel Leba, Monica Computer and System Control Engineering Department University of Petrosani 20 Universitatii Petrosani332006 Romania

ISBN: (纸本)9783031816840

This paper explores recent innovation in the field of robotic teleoperation, presenting a state-of-the-art system for a robotic arm, configurable as an exoskeleton or prosthetic limb. Based on noninvasive neural headset technology, the system captures movement intentions directly from the user’s neural activity. By precisely interpreting neural signals and translating them into robotic arm movements, the system bridges the gap between human intention and robotic action. Its uniqueness lies in its ability to interpret the subtleties of human intent through non-invasive means, providing intuitive and fluid control over the robotic arm. The system is distinguished by the efficient use of rich neural activity, thus improving usability and opening up new possibilities for people with mobility impairments. The paper analyzes technical complexities, detailing the functionality of neural headsets, signal decoding algorithms, and the command formation process for the robotic arm. It also presents empirical evidence of the effectiveness of the system and discusses possible applications and future improvements. This research not only contributes to robotic teleoperation, but also paves the way for more human and empathetic interactions with machines in the future. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Exoskeleton (Robotics)

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