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3rd IEEE international conference on Human-Machine Systems, ICHMS 2022

作者： Panagopoulos, Dimitris Petousakis, Giannis Ramesh, Aniketh Ruan, Tianshu Nikolaou, Grigoris Stolkin, Rustam Chiou, Manolis University of West Attica Industrial Design & Production Engineering Athens Greece Manchester United Kingdom Birmingham United Kingdom

ISBN: (数字)9781665452380

ISBN: (纸本)9781665452380

This paper presents a Mixed-Initiative (MI) framework for addressing the problem of control authority transfer between a remote human operator and an AI agent when cooperatively controlling a mobile robot. Our Hierarchical Expert-guided Mixed-Initiative control Switcher (HierEMICS) leverages information on the human operator's state and intent. The control switching policies are based on a criticality hierarchy. An experimental evaluation was conducted in a high-fidelity simulated disaster response and remote inspection scenario, comparing HierEMICS with a state-of-the-art Expert-guided Mixed-Initiative control Switcher (EMICS) in the context of mobile robot navigation. Results suggest that HierEMICS reduces conflicts for control between the human and the AI agent, which is a fundamental challenge in both the MI control paradigm and also in the related shared control paradigm. Additionally, we provide statistically significant evidence of improved, navigational safety (i.e., fewer collisions), LOA switching efficiency, and conflict for control reduction. © 2022 IEEE.

关键词： Human robot interaction

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An Overview for Computer-Assisted Automated Spinal Scoliosis Measurement 23

An Overview for Computer-Assisted Automated Spinal Scoliosis...

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Proceedings of the 3rd international conference on Electronic Information Technology and Smart Agriculture

作者： Aishu Xie Ervin Gubin Moung Faculty of Computer and Artificial Intelligence Huaihua University China and Faculty of Computing and Informatics University Malaysia Sabah Malaysia Faculty of Computing and Informatics University Malaysia Sabah Malaysia

ISBN: (纸本)9798400716775

Spinal X-rays are widely used for screening and preliminary diagnosis of adolescent scoliosis due to their low cost and minimal radiation exposure. To enhance the accuracy of scoliosis measurements and alleviate the burden on physicians, the goal in this field has been to achieve fully automated spinal curvature measurements under the assistance of computer technology. In this paper, an analysis is conducted on existing computer assisted methods for measuring scoliosis across various image modalities. These methods are categorized into three groups based on their contributions to the automation of scoliosis measurement: automated scoliosis localization, automated curvature feature extraction, and automated classification of scoliosis severity levels. In the end, the problems existing in the current research progress are highlighted and possible solutions are discussed for achieving fully automated measurement of spinal curvature on X-rays.

关键词： Curvature feature extraction Scoliosis localization Spinal curvature

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Solar-Powered Smart Wheelchair with Voice controller for Physically Challenged People

Solar-Powered Smart Wheelchair with Voice Controller for Phy...

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Advancements in Electrical, Electronics, Communication, Computing and automation (ICAECA), international conference on

作者： M. Karthik G. Hemalatha L. Sreevidya R. Deepalakshmi K Premalatha Department of Electrical and Electronics Engineering SRM Madurai College for Engineering and Technology Tamil Nadu India Department of Robotics and Automation Sri Ramakrishna Engineering College Coimbatore Tamil Nadu India Department of Electrical and Electronics Engineering V.S.B College of Engineering Technical Campus Coimbatore Tamil Nadu India Department of Computer Science Engineering SRM Madurai College for Engineering and Technology Tamil Nadu India Department of Electrical and Electronics Engineering Kumaraguru College of Technology Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

It is challenging for those with strong mental faculties but physical disabilities to get around in a conventional hand-powered wheelchair. This project will enable any existing wheelchair to have an inexpensive assembly that enables a smart motion automation system that can be controlled by speech recognition on a smartphone. Continuous operation is guaranteed by the dual-charging system, which also offers longer mobility without the need for frequent recharging and independence from external power outlets. This enables users to adjust to varying conditions by depending on solar power during the day and switching to battery charging when solar energy is scarce. The main concept is a smartphone with built-in Bluetooth connectivity and the Android operating *** the distribution of the application we have developed, the goal of our project may be extended to other mobile devices that run Android software. The second main component of our system design is the microprocessor, which drives the wheelchair's dc motor in different directions. The wheelchair may now travel in a variety of directions thanks to this. The suggested model operates autonomously and on its own.

关键词： automation Gears Navigation Wheelchairs Operating systems Wheels Solar energy DC motors Mobile handsets Telecommunication computing

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Physical Distancing System Using Computer Vision 3

Physical Distancing System Using Computer Vision

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3rd international conference on Cybernetics and Intelligent System (ICORIS)

作者： Kartikawati, Lili Nabawi, Isnan Rahayu, Vita Kusrini Ariatmanto, Dhani Ernawan, Ferda Univ AMIKOM Yogyakarta Master Informat Engn Yogyakarta Indonesia Univ Malaysia Pahang Fac Comp Coll Comp & Appl Sci Pahang Indonesia

ISBN: (纸本)9781665425803

The regulation of social distancing in standing queues such as queues at ATMs and queues for ordering fast food is very important to apply during COVID-19 pandemic. The system can control the discipline of keeping a distance which can reduce the rate of transmission of the Covid 19 virus. The system is expected to be able to handle supervision and regulation of the application of physical distancing by involving hardware input in the form of a camera, which will provide the condition of standing queue in the form of images to be processed to produce output information, the number of objects in the standing queue, the distance between objects and the x, y coordinates of the object in the standing queue. The final result of the Physical Distancing Warning System is able to maximize the distance control in standing queues such as queues at ATMs and queues for ordering fast food. Based on tests carried out able to detect human objects and calculate the distance between them. Tests to obtain the validity of system performance are carried out by varying the minimum threshold value. The best performance results are obtained at the minimum threshold value of 40 where the system error is 22.75%. The output of the computer vision process that is sent to the microcontroller as a command to the lights, servo and laser has been fully worked (100%) with the correctness of the response completely controlled by the processing results in the computer vision section.

关键词： Physical distancing computer vision and robotics

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Research on modular charging systems based on digital twins

Research on modular charging systems based on digital twins

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Power Electronics, Computer Applications (ICPECA), IEEE international conference on

作者： Qicheng Dong Zhigang Xu Junyi Wang Xiao Yang Linlin Fan Wei Li College of Mechanical and Electrical Engineering Shenyang Aerospace University Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Institute of Robotics and Intelligent Manufacturing Innovation Chinese Academy of Sciences Shenyang China Northwestern Industries Group Co. Ltd Xi’an China

The development of ammunition loading technology plays a vital role in the improvement of my country's national defense construction level. Compared with the traditional charge, the modular charge has the advantages of high interchangeability and modularity, and can realize the rapid filling of the charge. However, for the application of modular charging technology, when building unit modules, it is still necessary to manually teach the charging target point, and the modular charging technology has the disadvantage of being difficult to adapt to flexibility. Therefore, in the face of the diversity of ammunition, modular charge is not conducive to the rapid and efficient production of ammunition. The current automation technology is difficult to improve the flexible adaptability of modular charge. Aiming at the disadvantages of modular charging technology, a modular flexible charging system based on digital twin is proposed, including the construction of virtual charging workstation, key point identification, automatic trajectory generation and automatic robot program generation. The system greatly improves the production efficiency of modular charge, provides a reference for the research of modular flexible charge, and improves the digital manufacturing level of ammunition production.

关键词： Drugs Robot kinematics Loading Production Power electronics Filling Digital twins

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Latent 3D Scene Graph with Aligned Visual-Language Perception for Object-Goal Navigation

Latent 3D Scene Graph with Aligned Visual-Language Perceptio...

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Mechatronics, control and robotics (ICMCR), international conference on

作者： Jianwei Zhang Kang Zhou Junjie Yang Xiaojian Li College of Engineering Southern University of Science and Technology Shen Zhen China School of Computer Science City University of Hong Kong Hong Kong China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shen Zhen China

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

Object-goal navigation requires agents to accurately locate and navigate to specified target objects in complex indoor environments. Existing methods primarily rely on single visual observations or simple semantic matching, making it difficult to effectively understand 3D scene relationships between target objects, which leads to inefficient path planning during navigation. Furthermore, the feature discrepancy between visual and language modalities poses challenges for accurate target identification. To address these issues, we propose Latent 3D Scene Graph with Aligned Visual-Language Perception (LSGAP), a novel approach that explicitly models 3D scene relationships between objects through depth perception and latent 3D scene graph construction. Meanwhile, we leverage multimodal pretraining strategies to achieve effective visual-language feature alignment, enhancing the model's target recognition capabilities. This end-to-end architectural design improves spatial cognition ability and enables more efficient navigation decision-making. We conduct extensive experimental evaluations in the AI2THOR interactive environment to validate the effectiveness of our navigator.

关键词： Visualization Solid modeling Three-dimensional displays Systematics Navigation Target recognition Semantics Indoor environment Standards Robots

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Enhancing Extrusion Precision and Reliability in Robotic Multi-Axis Additive Manufacturing through Digital Twin Integration

Enhancing Extrusion Precision and Reliability in Robotic Mul...

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international conference on control, automation and Systems ( ICCAS)

作者： Tomáš Jochman Václav Voltr Ondřej Švec Václav Kubáček Pavel Burget Václav Hlaváč Department of Cybernetics Faculty of Electrical Engineering Czech Technical University in Prague Prague Czech Republic Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague Czech Republic

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

In robotic multi-axis additive manufacturing, achieving high precision and consistency is crucial. This paper presents a comprehensive calibration procedure and optimization strategy for process parameters in a filament-based extruder mounted on an industrial robot. A digital twin of the manufacturing setup is utilized to simulate and validate the process, enabling precise adjustments and automation of code generation for robotic operations. Experimental calibration artifacts are produced and measured to verify the effectiveness of the proposed approach, highlighting the impact of variables such as hot-end temperature, layer height, and tool center point velocity on print quality. A laser tracker is employed to ensure precise measurement of calibration artifacts, enhancing the accuracy of the calibration process. The results highlight the potential for advancements in the precision and reliability of multi-axis additive manufacturing processes through systematic calibration and optimization, enabling the stable production of complex 3D-printed structures and reduced production waste.

关键词： Temperature measurement Accuracy Systematics Service robots Production Three-dimensional printing Calibration Manufacturing Robots Optimization

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Artificial Intelligence is Used to Identify Tomato Diseases Through Leaf Analysis

Artificial Intelligence is Used to Identify Tomato Diseases ...

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informatics, Electronics, and Radio Engineering (PIERE), international conference Problems of

作者： Otabek Khujaev Odamboy Djumanazarov Bobur Soliyev IT Department Urgench branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Urgench Uzbekistan

ISBN: (数字)9798331516321

ISBN: (纸本)9798331516338

This paper explores using artificial intelligence in applications to detect tomato leaf diseases. A key issue is how automated systems and artificial intelligence can be used to diagnose and predict disease control, damage, and temporary control of tomato diseases. The paper is based on the study of the benefits of implementing classical and modern artificial intelligence models, their problems, and successful technological solutions in detecting tomato diseases. The article describes in detail how effective distributed artificial intelligence algorithms are in detecting tomato diseases, their application, and their independence in analyzing and accounting for the results. As a result, it is important to use artificial intelligence to detect tomato leaf diseases quickly, and this discovery offers effective methods for faster treatment. Tomato export is considered important for the economy of Uzbekistan, one of the developing agricultural countries today. However, even in this area, there are cases of crop loss, so we created and analyzed a project that detects tomato leaf diseases based on deep learning with transfer learning architectures.

关键词： Deep learning Biological system modeling Transfer learning Prediction algorithms Mobile applications Medical diagnosis Artificial intelligence Usability informatics Diseases

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A Nomogram Approach with Logistic Regression and Naïve Bayes to Identify Chronic Kidney Disease on Diabetes Type 2

A Nomogram Approach with Logistic Regression and Naïve Baye...

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international conference on Smart Cities, automation & Intelligent Computing Systems (ICON-SONICS)

作者： I Made Murwantara Andriyani Graduate Informatics Dept. Universitas Pelita Harapan Jakarta Indonesia Diploma in Pharmacy Dept. Universitas Pelita Harapan Jakarta Indonesia

A novel Nomogram model, integrating both logistic regression and na39;ve bayes methodologies, exhibits a promising capability in deciphering the molecular indicators of chronic kidney disease triggered by diabetes ...

A novel Nomogram model, integrating both logistic regression and naïve bayes methodologies, exhibits a promising capability in deciphering the molecular indicators of chronic kidney disease triggered by diabetes type 2 symptoms. This study employs the nomogram technique to pinpoint the manifestation of chronic kidney disease linked to elevated blood sugar levels. We meticulously examined molecular imaging of rat kidney tissues, identifying the presence of GLUT9 and SGLT2. Their presence is crucial as they instigate an increase in glucose re-absorption in the kidneys, fast-tracking kidney deterioration. The Nomogram model stands out by efficiently computing class probabilities based on distinct attributes. These attributes are derived from quantified observations of Tubules Proximal and Tubules Distal in rat kidneys, all stemming from meticulous wet lab experiments. Utilizing domain expert insights, we identified pivotal molecular traces for our investigation. To ascertain the prevalence of chronic disease in rats, the gathered dataset underwent classification through logistic regression and naïve bayes algorithms. The subsequent representation through the Nomogram model delivered an interactive and detailed analysis. Our results underscore the Nomogram’s superior performance in detecting symptoms relying on the applied classifiers.

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Autonomous Ground Navigation in Highly Constrained Spaces: Lessons learned from The 3rd BARN Challenge at ICRA 2024

arXiv

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arXiv 2024年

作者： Xiao, Xuesu Xu, Zifan Datar, Aniket Warnell, Garrett Stone, Peter Damanik, Joshua Julian Jung, Jaewon Deresa, Chala Adane Huy, Than Duc Jinyu, Chen Yichen, Chen Cahyono, Joshua Adrian Wu, Jingda Mo, Longfei Lv, Mingyang Lan, Bowen Meng, Qingyang Tao, Weizhi Cheng, Li George Mason University United States The University of Texas Austin United States Army Research Laboratory United States Sony AI Japan Korea Republic of Singapore Hong Kong

The 3rd BARN (Benchmark Autonomous Robot Navigation) Challenge took place at the 2024 IEEE international conference on robotics and automation (ICRA 2024) in Yokohama, Japan and continued to evaluate the performance of state-of-the-art autonomous ground navigation systems in highly constrained environments. Similar to the trend in The 1st and 2nd BARN Challenge at ICRA 2022 and 2023 in Philadelphia (North America) and London (Europe), The 3rd BARN Challenge in Yokohama (Asia) became more regional, i.e., mostly Asian teams participated. The size of the competition has slightly shrunk (six simulation teams, four of which were invited to the physical competition). The competition results, compared to last two years, suggest that the field has adopted new machine learning approaches while at the same time slightly converged to a few common practices. However, the regional nature of the physical participants suggests a challenge to promote wider participation all over the world and provide more resources to travel to the venue. In this article, we discuss the challenge, the approaches used by the three winning teams, and lessons learned to direct future research and competitions. © 2024, CC BY.

关键词： Navigation systems

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