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Bringing the new class of cable-driven parallel robots to the world of industrial cyber-physical systems based on RAMI 4.0 5

Bringing the new class of cable-driven parallel robots to th...

引用

ieee 5th international conference on Industrial cyber-Physical systems (ICPS)

作者： Walter, Jonas Grau, Simon Raczok, Tobias Reitelshoefer, Sebastian Franke, Joerg Friedrich Alexander Univ Erlangen Nurnberg Inst Factory Automat & Prod Syst Erlangen Germany

ISBN: (纸本)9781665497701

Adaptive robots are a crucial factor for small-batch manufacturing. In this context, the new class of cable-driven parallel robots (CDPRs) represents a promising technology that provides highly dynamic manipulation, reconfigurability, and variable stiffness. However, there is no approach consistent with the Reference Architecture Model Industrie 4.0 (RAMI 4.0) that enables the networking of these robots and their integration into a smart factory consisting of numerous industrial cyberphysical systems (ICPS). The contribution of this paper is a novel integration architecture for CDPRs in accordance with RAMI 4.0. We focus on two points to advance the vision of integrated and networked CDPRs. First, we provide an accessible way to the working principle of CDPRs by explaining their setup, behavior, and control. Second, we define an asset administration shell for CDPRs based on the RAMI 4.0 preferred standard Open Platform Communications Unified Architecture (OPC UA) to achieve semantic interoperability. We finally validate our work using a cable-driven robotic joint as a proof-of-concept.

关键词： Industries Parallel robots Service robots conferences Semantics cyber-physical systems Standards

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Machine Learning Classification of Riemannian Tangent Spaces Based on MI-BCI 20

Machine Learning Classification of Riemannian Tangent Spaces...

引用

20th ieee international conference on Mechatronics and automation, ICMA 2023

作者： Zhao, Chunli Dong, Enzeng Tong, Jigang Yang, Sen Du, Shengzhi Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Intelligent Robot Laboratory 391 Binshui West Road Tianjin China Tshwane University of Technology Department of Electrical Engineering Pretoria0001 South Africa

ISBN: (纸本)9798350320831

Motor imagery brain-computer interfaces (BCIs) have been extensively used in stroke rehabilitation, particularly in China where stroke incidence is high. The application of BCI to control prostheses and robotic arms has shown promising results in improving the quality of life for stroke patients. However, a major challenge in this field is improving the accuracy of motor imagery (MI) classification. Several previous studies have reported that stroke patients exhibit atypical patterns of even-trelated desynchronization (ERD) and event-related synchronization (ERS) activation during motor imagery (MI) tasks. It has been suggested that the brain regions affected by stroke may show reduced excitability and relative insensitivity to external interference compared to those of healthy individuals. Therefore, this study proposes that the classification accuracy of stroke patients in the same MI task would be higher compared to that of healthy volunteers. In this study, we employed a feature extraction algorithm that combines the Filter Bank Common Spatial Pattern (FBCSP) and Riemann geometric mean distance methods to compare the classification accuracy of five different classifiers, with the objective of identifying the most suitable classifier for our analysis. The obtained results revealed that the K-Nearest Neighbors (KNN) classifier yielded the highest accuracy, reaching 87.5% for stroke patients and 85% for healthy volunteers, respectively. In addition to accuracy, we also utilized Kappa values as evaluation metrics, which yielded Kappa results of 0.619 and 0.613 for stroke patients and healthy volunteers, respectively. © 2023 ieee.

关键词： Brain computer interface

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automation of Enforcer Agent Installation

Automation of Enforcer Agent Installation

引用

2023 international conference on Innovative Computing, intelligent Communication and Smart Electrical systems, ICSES 2023

作者： Sundareswaran, T.V. Karunakaran, Kavitha Raju, Kannan Bethanney Janney, J. Jebaraj Solomon, Ezekiel Chennai India Sathyabama Institute of Science and Technology Department of Biomedical Engineering Chennai India

ISBN: (纸本)9798350319200

As a part of an organizational initiative to move towards a zero-trust model, The proposed study analyses a number of solutions for hosts that are physical or in legacy models to be compatible with the micro-segmentation of endpoint hosts. One of the solutions, that would be considered for testing would be to install the enforcer agents and build over a Palo Alto network solution for physical/virtual servers. Installing the agents on the endpoint hosts for the Linux (RHEL kernel), Red Hat/CentOS and Windows hosts are a bit cumbersome and the success rate is very low. It is not feasible to install it on multiple hosts at the same time. Hence an automated agent installation is used to fix the aforementioned vulnerability. The aim of the work is expected to develop a single-click automation interface that facilitates concurrent agent installation on many hosts. After installation, the resource utilization of the legacy and micro-segmentation agents with their respective policies are compared. The installation success rate was 90-95% based on testing, and resource utilization was adequate. © 2023 ieee.

关键词： Agent Installation Authentication Authorization services Cloud Management Endpoint Host

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Artificial Intelligence In cybersecurity Applications

Artificial Intelligence In Cybersecurity Applications

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ieee international conference on intelligent Engineering systems (INES)

作者： Anni Dasho Sharko Genci Sharko Silvana Qose Faculty of Information Technology & Innovation Luarasi University Tirana Albania Faculty of Electrical Engineering Polytechnic University of Tirana Tirana Albania Doctoral School on Safety and Security Sciences Obuda University Budapest Hungary

ISBN: (数字)9798350367591

ISBN: (纸本)9798350367607

People cannot handle the volume of data and the complexity of processes needed to secure cyberspace without significant automation. However, it is challenging to develop technologies and software with conventional fixed implementations (hardwired decision-making logic) that successfully defend against security risks. AI learning techniques and machine simplicity can be used to treat this issue. Artificial intelligence (AI) approaches have been attempted to be used in a variety of cyber security applications recently. This paper gives an overview to the algorithms that might be used to have a better protection for our systems. This paper examines the crucial role that artificial intelligence plays in cybersecurity, as well as its benefits, drawbacks, and practical applications from the largest global corporations, such as PayPal and AWS. Also gives the benefits of using AI technology for Security.

关键词： Decision making cyberspace Manuals Malware Hazards Logic Internet of Things

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Motion Is All You Need 6

Motion Is All You Need

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6th international conference on intelligent control, Measurement and Signal Processing, ICMSP 2024

作者： Yang, Shuangye Gu, Zhenyue Xu, Yuanqing Zhang, Junhao Yan, Bintao Ai, Wei Guo, Biao Zhang, Hongwei Beijing Petroleum Machinery Co. Ltd. Department of Information Center Beijing China Beijing Institute of Technology School of Medical Technology Beijing China Nanyang Technological University Department of Electrical and Electronic Engineering Singapore Singapore Tianjin University of Technology Maritime College Tianjin China

ISBN: (纸本)9798331516550

The integration of digital tablets and smart pens has revolutionized handwriting tasks in various domains, yet current solutions like the Apple Pencil necessitate specialized touchscreens, escalating costs and limiting accessibility. This study introduces a novel motion-based handwriting recognition system that eliminates the dependency on touchscreens by utilizing motion data alone, enabling handwriting capture on any surface. Our primary contributions include the design of an all-in-one, 3D-printed smart pen prototype equipped with an inertial measurement unit (IMU) for precise motion sensing, and the creation of a comprehensive handwriting motion dataset comprising 6,500 samples of lowercase English characters. We developed end-to-end machine learning algorithms, specifically a 1D Convolutional Neural Network (1D CNN) and a Long Short-Term Memory (LSTM) network, to accurately recognize handwritten characters from the captured motion data. Experimental results demonstrate that our LSTM model achieves a test accuracy of 90.46%, significantly outperforming previous motion-based recognition systems. This work validates the feasibility of motion-only handwriting recognition and presents a cost-effective alternative to touchscreen-dependent smart pens, potentially broadening the accessibility of digital handwriting technologies. © 2024 ieee.

关键词： Convolutional neural networks

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Low-Dose Sinogram Restoration in SPECT Imaging Based on Conditional Generative Adversarial Network and LSTM. 23

Low-Dose Sinogram Restoration in SPECT Imaging Based on Cond...

引用

15th international conference on Machine Learning and Computing, ICMLC 2023

作者： Peng, Limei Li, Si School of Computer Science and Technology Guangdong University of Technology China

ISBN: (纸本)9781450398411

To address the problem that low-dose SPECT imaging will lead to poor-quality projection images, we propose a network structure based on the conditional generative adversarial network and add a convolutional LSTM module to combine the sequence features of sinograms for low-dose SPECT sinogram restoration, called LCGAN, the spatial and angular information of the sinogram can be better utilized. Projection data from SIMIND software simulations are used to train the proposed model. The recovered sinograms were reconstructed using the model-based iterative reconstruction (MBIR) method. To evaluate the effectiveness of the LCGAN model, the reconstructed images were evaluated using the global metrics PSNR and NMSE and the local metrics COV, and the results showed that the proposed method significantly improved the reconstruction quality of the low-dose sinograms. © 2023 ACM.

关键词： Quality control

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A Novel 4D Radar and Image Fusion for 3D Object Detection in Autonomous Driving 27

A Novel 4D Radar and Image Fusion for 3D Object Detection in...

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27th ieee international conference on intelligent Transportation systems, ITSC 2024

作者： Zhao, Yang Jin, Yiwei Deng, Ruoyu Tao, Yueming Peng, Zhinan Zhan, Huiqin Cheng, Hong School of Automation Engineering University of Electronic Science and Technology of China Sichuan Chengdu China Chengdu Technological University Chengdu611730 China

ISBN: (纸本)9798331505929

3D object detection is a crucial task in the perception module of autonomous driving, current research employs LiDAR or imagery for 3D object detection. However, imagery lacks depth information, and LiDAR has limited robustness in adverse weather conditions. 4D millimeter-wave radar, as a promising new type of sensor, not only provides high-precision Doppler velocity information but also, with enhanced elevation resolution, can obtain accurate height information of targets. Compared to high-beam LiDAR, the point cloud is still sparse, making it challenging to obtain precise semantic information, thus posing a significant challenge for 3D object detection using 4D millimeter-wave radar. This paper introduces a 3D object detection framework that fuses 4D millimeter-wave radar with imagery-4D Radar Fusion. By transforming both 4D millimeter-wave radar and monocular imagery into the BEV space for feature fusion, it effectively enhances the semantic information learning of the 4D millimeter-wave radar. Experimental evaluation on the autonomous driving dataset VoD demonstrates the effectiveness of 4D Radar Fusion, achieving a 6% improvement in 3D average precision over the baseline for the entire annotated area. © 2024 ieee.

关键词： Image fusion

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High-Speed Aircraft Swarm Collaboration Method

High-Speed Aircraft Swarm Collaboration Method

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2023 ieee international conference on Unmanned systems, ICUS 2023

作者： He, Fan Hu, Yanyang School of Astronautics Harbin Institute of Technology Harbin China

ISBN: (纸本)9798350316308

Facing the future all-area fast-time response combat demand, the high-speed aircraft swarm system is bound to develop in the direction of intelligence. Considering the uninterpretable problem of reinforcement learning in practical applications, the safe reinforcement learning theory is introduced into the intelligent decision-making problem of aircraft swarm, and the improved soft actor-critic algorithm is proposed based on the Lyapunov stability theory. Firstly, a high-speed vehicle dynamics model is established with normal overload as the control quantity. Secondly, the task is divided into three parts: target striking, formation keeping, and threat zone avoidance, and the vehicle guidance reward function is designed. Finally, by comparing the training results with those of the actor-critic algorithm, it is concluded that the method can enable the agent to maintain a low safety cost throughout the training process. © 2023 ieee.

关键词： Reinforcement learning

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Enhancing Self-Driving control and Sensing systems with Cloud Computing ING with AI and BD 4

Enhancing Self-Driving Control and Sensing Systems with Clou...

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4th ieee international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Awasthi, Aviral Issa, Ali Ashoor Mohsen, Abdul Hussein Al-Jawahry, Hassan M. Jweeg, Muhsin Alwan, Ali Saad Graphic Era Hill University Department of Computer Science and Engineering Uttarakhand Bhimtal India National University of Science and Technology College of Technical Engineering DhiQar64001 Iraq Alkunooze University College Computer Engineer Department Basra Iraq The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq Al-Farahidi University Baghdad Iraq Kut University College Business Administration Department wasit Al kut52001 Iraq

ISBN: (纸本)9798350360165

A vast amount of research has been done on vehicular networking because it is continuously required for infotainment, safety, efficient traffic management, and normalization. As the vehicles are installed with various communication systems, computer power, storage, and enhanced sensing capabilities, the ITS is continually updating. Vehicular Cloud Computing (VCC) is one of the fundamental techniques that assimilate the vehicle resources not only to the problems of the vehicular networks but also to make fast decisions. The article discusses a complete and state-of-the-art survey of VCC along with its categorization, making attention to its use, cloud configurations, critical management, inter-cloud communication, and privacy/security issues. We develop a VCC framework while considering the previous work, contrasting it with traditional CC and giving emerging issues of the work. VCC is practically and profitably reformed in the literature, and it credits the intelligent vehicular networks for making the autonomous traffic, advanced vehicle control, and sophisticated sensing systems. © 2024 ieee.

关键词： Advanced vehicle control systems

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A force-aware reproduction-based workspace mapping method for human-computer cooperative systems 2

A force-aware reproduction-based workspace mapping method fo...

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2nd international conference on Robotics, Artificial Intelligence and intelligent control, RAIIC 2023

作者： Qian, Weimin Liu, Manlu Zhang, Qingbo Huang, Lin Southwest University of Science and Technology School of Information Engineering Mianyang621010 China

ISBN: (纸本)9798350328004

To enhance the robustness and proximity of robotic arm motion in human-machine cooperative systems, a master-slave workspace mapping method for human-machine cooperative systems based on force awareness in the present is proposed in the paper. The method utilizes a man-machine cooperative system composed of master-slave heterogeneous robotic arms, adds joint mapping algorithm based on the hybrid mapping algorithm of rate and position, and defines drift region and operation region at the master end to ensure the stability of the system. Meanwhile, the virtual workspace of the robotic arm at the main end is fed back to the operator in the form of haptics by using force sense reproduction technology, which enhances the sense of presence of the system operation and achieves precise and efficient remote operation under the limited working space. Finally, the proposed method is validated on the experimental platform of the built system. The experimental results demonstrate that the mapping method can enable the man-machine cooperative system composed of master-slave heterogeneous robotic arms to have a larger working space utilization, better path following and target localization, and realize the continuous motion control of the system. © 2023 ieee.

关键词： Robotic arms

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