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8th IEEE International Conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Liu, Xiaobo Wan, Fang Ge, Sheng Wang, Haokun Sun, Haoran Song, Chaoyang Southern University of Science and Technology Department of Mechanical and Energy Engineering Guangdong Shenzhen518055 China School of Design Southern University of Science and Technology Guangdong Shenzhen518055 China Hong Kong University of Science and Technology Robotics & Autonomous Systems Thrust System Hub Hong Kong Hong Kong The University of Hong Kong Department of Computer Science Hong Kong Hong Kong

ISBN: (纸本)9798350300178

Benchmarking provides experimental evidence of the scientific baseline to enhance the progression of fundamental research, which is also applicable to robotics. In this paper, we propose a method to benchmark metrics of robotic manipulation, which addresses the spatial-temporal reasoning skills for robot learning with the jigsaw game. In particular, our approach exploits a simple set of jigsaw pieces by designing a structured protocol, which can be highly customizable according to a wide range of task specifications. Researchers can selectively adopt the proposed protocol to benchmark their research outputs, on a comparable scale in the functional, task, and system-level of details. The purpose is to provide a potential look-up table for learning-based robot manipulation, commonly available in other engineering disciplines, to facilitate the adoption of robotics through calculated, empirical, and systematic experimental evidence. © 2023 IEEE.

关键词： Benchmarking

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Development of Detection Kidney Function Stand Alone System and design based on Oral Ammonia Levels

Development of Detection Kidney Function Stand Alone System ...

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International Conference of Computer and Informatics engineering (IC2IE)

作者： William Natasha Angeline Hansen Yosica Mariana Elioenai Sitepu Winda Astuti Melinda Siswanto Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Product Design Program Industrial Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Industrial Engineering Department BINUS Graduate Program Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia Biotechnology Engineering Department Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331505530

ISBN: (纸本)9798331505547

The development of detection kidney function system at the first prototype have problem with the dependence on the internet, which make not practical in the development of the system and the initial design was not ergonomic. In this work the development of the second step is done with the improvement of accuracy compared with other methods. In this work the new design of the embedded system is also applied and in term of algorithm, the system applied for woman patient. Three different types of machine learning techniques, namely K-nearest neighbors (KNN), Decision Tree and Random Forest are applied and compared. The AI-based kidney failure severity identification system with KNN algorithm had an average accuracy of 90% and 91% for training and testing accuracy, respectively. The design of the embedded system also renews with stylist, simple and practical.

关键词： Training Accuracy Machine learning algorithms Embedded systems Nearest neighbor methods Vectors Decision trees Kidney Random forests Testing

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Deep Learning based Infrared Small Object Segmentation: Challenges and Future Directions

arXiv

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arXiv 2025年

作者： Yang, Zhengeng Yu, Hongshan Zhang, Jianjun Tang, Qiang Mian, Ajmal College of Engineering and Design Hunan Normal University Hunan Changsha410081 China School of Robotics Hunan University Hunan Changsha410082 China Department of Computer Science The University of Western Australia PerthWA6009 Australia

Infrared sensing is a core method for supporting unmanned systems, such as autonomous vehicles and drones. Recently, infrared sensors have been widely deployed on mobile and stationary platforms for detection and classification of objects from long distances and in wide field of views. Given its success in the vision image analysis domain, deep learning has also been applied for object recognition in infrared images. However, techniques that have proven successful in visible light perception face new challenges in the infrared domain. These challenges include extremely low signal-to-noise ratios in infrared images, very small and blurred objects of interest, and limited availability of labeled/unlabeled training data due to the specialized nature of infrared sensors. Numerous methods have been proposed in the literature for the detection and classification of small objects in infrared images achieving varied levels of success. There is a need for a survey paper that critically analyzes existing techniques in this domain, identifies unsolved challenges and provides future research directions. This paper fills the gap and offers a concise and insightful review of deep learning-based methods. It also identifies the challenges faced by existing infrared object segmentation methods and provides a structured review of existing infrared perception methods from the perspective of these challenges and highlights the motivations behind the various approaches. Finally, this review suggests promising future directions based on recent advancements within this domain. Copyright © 2025, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Cryo-CACTI: Cryogenic-Aware CACTI for Cache Modeling down to 10K in Advanced 7nm FinFETs

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IEEE Transactions on Computers 2025年

作者： Ravipati, Divya Praneetha van Santen, Victor M. Parihar, Shivendra Singh Chauhan, Yogesh Singh Panda, Preeti Ranjan Amrouch, Hussam Indian Institute of Technology Delhi Department of Computer Science and Engineering New Delhi India Technical University of Munich TUM School of Computation Information and Technology Chair of AI Processor Design Munich Institute of Robotics and Machine Intelligence Germany Kanpur Nanolab Department of Electrical Engineering Uttar Pradesh India

Cryogenic circuits are currently employed in fields such as quantum computing, particle detectors, magnetic resonance imaging, and space applications. While cryogenic circuits are being researched, there is limited work on designing cryogenic caches at temperatures below 77K. Moreover, there is no tool to estimate the delay, power, and area of cryogenic caches at advanced technology nodes. Our research focuses on the development of cryogenic caches tailored for the 7nm technology node, operating at 10K. However, a key challenge is the lack of cryogenic measurement data, especially in recent technologies. Consequently, through conducting our own FinFET transistor measurements, we calibrate cryogenic transistor models at 10K. With the 7nm cryogenic transistor data, we model Cryo-CACTI for cryogenic caches (due to cache’s vital role in improving performance and their considerable share in area and power of the processor). Using Cryo-CACTI, our evaluation reveals considerable improvements in the energy efficiency (up to 99%) of cryogenic caches of larger sizes compared to the caches at room temperature (300K). Additionally, we explore alternative cache configurations at circuit-level to optimize cryogenic operation. Furthermore, we use Cryo-CACTI to explore the performance/energy consumption of cryogenic caches while simulating workloads such as SPEC CPU2017 and machine learning via neural networks. © 1968-2012 IEEE.

关键词： Combinatorial circuits

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designing an Ultrasonic System Used to Reduce the Cross-Linking Time of Epoxy Resins Used in the Construction of Brake Cylinders

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Macromolecular Symposia 2024年第3期413卷 2300206-2300206页

作者： Pasare, Vili Nitoi, Dan Opran, Constantin G. Chivu, Oana Semenescu, Augustin Milicescu, Stefan Faculty of Industrial Engineering and Robotics Department of Engineering Graphics and Industrial Design National University of Science and Technology Politehnica of Bucharest 313 Splaiul Independentei Bucharest060042 Romania University of Medicine and Pharmacy Carol Davila Bucharest Bulevardul Eroii Sanitari Nr. 8 Sector 5 Bucuresti Romania

Ultrasounds and their applications constitute fields of theoretical and practical research with applicability starting with the military, medicine, automotive industry, and ending with household appliances. The use of ultrasonic field in the cross-linking of epoxy resins reduces the time required to produce composite structures, independent of the type of reinforcing components used. Brake cylinders, made by successive deposition of two layers of epoxy resin and quartz sand used in applications where frictional forces are very high, constitute a challenge for composite structures. The article presents the analytical calculation and the design of the ultrasonic system used in making a sample made of metallic base material and two layers of epoxy resin reinforced with quartz sand. Using this new proposed technology, there is a substantial reduction in the time required to solidify the structure and the elimination of the need for a high temperature necessary to carry out the traditional technological process. © 2024 Wiley-VCH GmbH.

关键词： Quartz

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IMPS: Informative Map Point Selection for Visual-Inertial SLAM

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第9期9卷 5595-5605页

作者： Changxiang Liu Hongshan Yu Qiang Fu Xieyuanli Chen Naveed Akhtar Zhi-Hong Mao College of Electrical and Information Engineering School of Robotics Quanzhou Institute of Industrial Design and Machine Intelligence Innovation Hunan University Changsha China National University of Defense Technology Changsha China School of Computing and Information Systems University of Melbourne Melbourne VIC Australia Department of Electrical and Computer Engineering University of Pittsburgh Pittsburgh PA USA

Visual-inertial SLAM (VINS) stands at the forefront of advancements in computer vision, robotics, and autonomous driving, revolutionizing the way we perceive and navigate the world. The typical approach in optimization-based methods for VINS is to estimate camera poses by minimizing the reprojection errors of all corresponding map points. However, not all map points are suitable for accurate pose estimation. Some map points introduce noise and can compromise the accuracy of the estimation. Current methods primarily focus on removing 2D noise points, which proves to be ineffective since triangulation can increase the uncertainty of map points. To address this problem, we propose a new method for Informative Map Point Selection (IMPS) in VINS systems. IMPS identifies the most informative map points by utilizing mutual and geometric information as the optimization target. We integrate IMPS into a VINS system and evaluate its performance using publicly available EuRoC, TUM and M2DGR datasets, as well as our own data. Experimental results demonstrate that our method surpasses existing VINS methods and achieves state-of-the-art pose estimation performance. Importantly, IMPS functions as an independent module with strong generalization capabilities, allowing for easy integration into other VINS systems and enhancing pose estimation performance. This integration not only elevates pose estimation accuracy but also holds great promise for advancing applications in intelligent driving and unmanned systems.

关键词： Simultaneous localization and mapping Optimization Cameras Pose estimation Robots Mutual information Intelligent vehicles

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Prototype of Turbine Propulsion System with Controllable Thrust Vector for Long-Range Unmanned VTOL Aircraft 21st

Prototype of Turbine Propulsion System with Controllable Thr...

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21st Polish Control Conference, PCC 2023

作者： Czyba, Roman Lemanowicz, Marcin Domin, Jaroslaw Grzybowski, Jacek Stępień, Izabela Ungier, Lukasz Rosiek, Radoslaw Bialas, Piotr Niemiec, Michal Department of Automatic Control and Robotics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology ul. Akademicka 16 Gliwice44-100 Poland Department of Chemical Engineering and Process Design Faculty of Chemistry Silesian University of Technology ul. Ks. M. Strzody 7 Gliwice44-100 Poland Department of Mechatronics Faculty of Electrical Engineering Silesian University of Technology ul. Akademicka 10a Gliwice44-100 Poland

ISBN: (纸本)9783031351723

The aim of the project was to build a prototype of a turbine drive with a controllable thrust vector for a long-range vertical take-off and landing (VTOL) aircraft. The construction of the prototype required the development of a vectoring system for the tail propulsion system and a dedicated VTOL aircraft stabilization and control system. The prototype of the turbine drive system was based on energy-efficient electric motors. Research also involved modeling the turbine propulsion aerodynamics with usage of computational fluid dynamics (CFD) analysis. As a result of the design stage, a prototype of the propulsion system was created, on which flight tests were carried out. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computational fluid dynamics

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Collaborative Fall Detection and Response Using Wi-Fi Sensing and Mobile Companion Robot

Collaborative Fall Detection and Response Using Wi-Fi Sensin...

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IEEE International Conference on robotics and Biomimetics

作者： Yunwang Chen Yaozhong Kang Ziqi Zhao Yue Hong Lingxiao Meng Max Q.-H. Meng Shenzhen Key Laboratory of Robotics Perception and Intelligence Southern University of Science and Technology Shenzhen China Department of Electrical and Electronic Engineering SUSTech Shenzhen China School of System Design and Intelligent Manufacturing SUSTech Shenzhen China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

This paper presents a collaborative fall detection and response system integrating Wi-Fi sensing with robotic assistance. The proposed system leverages channel state information (CSI) disruptions caused by movements to detect falls in non-line-of-sight (NLOS) scenarios, offering non-intrusive monitoring. Besides, a companion robot is utilized to provide assistance capabilities to navigate and respond to incidents autonomously, improving efficiency in providing assistance in various environments. The experimental results demonstrate the effectiveness of the proposed system in detecting falls and responding effectively.

关键词： Navigation Biomimetics Collaboration Robot sensing systems Sensors Fall detection Wireless fidelity Monitoring Injuries Channel state information

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Integration of Computer Vision in A Testing Facility for Prosthetic Joint Inspection and Performance Assessment 24

Integration of Computer Vision in A Testing Facility for Pro...

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24th International Conference on Mechatronics Technology, ICMT 2021

作者： Glanville, Stephen Chong, Jun Jie Jafari, Aghil Etoundi, Appolinaire University of the West of England Faculty of Environment and Technology Health and Applied Sciences Bristol Robotics Laboratory Bristol United Kingdom Newcastle University Faculty of Mechanical Design and Manufacturing Engineering Singapore038986 Singapore University of the West of England Department Engineering Design and Mathematics Bristol United Kingdom University of the West of England Department Engineering Design and Mathematics Bristol United Kingdom

ISBN: (纸本)9781665424592

This paper presents a computer vision system within a test facility for prosthetic joint inspection and performance by analysing range of motion data. Testing with individuals rather than using a testing facility can cause issues, such as irritation, pain and rubbing of the residual limb. The use of a computer vision system within a testing facility can assess the performance of a prosthetic device by capturing video, images, and calculating angle data for range of motion. Other benefits of using a testing facility include reduced testing times and energy for the end user and the ability to test rigorously. It can be concluded that the computer vision system can capturing accurate angle data for use within the testing facility. However, a discrepancy between 0.55 and 0.6 degrees was found when comparing the angle of the knee joint in the computer aided design model to the built environment. Further development of the code and the use of masking with colour coded targets would result in more accurate angle calculation and automation. © 2021 IEEE.

关键词： Joints (anatomy)

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Development of ADL Motion Database to Promote Co-creative Care Support

Development of ADL Motion Database to Promote Co-creative Ca...

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SICE Annual Conference

作者： Kohei Okabe Kenji Kato Naoyuki Kubota Yasuhisa Hirata Mechanical System Safety Research Group JNIOSH Tokyo Japan Lab Clinical Evaluation with Robotics National Center for Geriatrics and Gerontology Nagoya Japan Department of Mechanical Systems Engineering Graduate School of Systems Design Tokyo Metropolitan University Tokyo Japan Department of Robotics Graduate School of Engineering Tohoku University Sendai Japan

This paper introduces fundamental development of a new database of activities of daily living (ADL) for the purpose of supporting independent care for the elderly or disabilities with adaptable AI-enable robots. The main concept of AI-robots is briefly illustrated. According to the concept of AI-robots, a simple framework to deal with ADL in aspect of both subjective and objective is demonstrated to achieve goal-oriented care support. The patient centric support is expected to prevent excessive care by the AI-robots. In order to perform the care support, the activities or motions defined as Doing-ADL that elderly people usually perform are digitalized as motion data. A method of utilizing a database system that accumulates such motion data is conceptually shown. Furthermore, the operation of the system as a digital platform for inclusive social care is proposed from the viewpoint of co-creation among care recipients, care workers and the AI-enabled robots.

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