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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Li, Zhihao Liu, Junjia Li, Zhuo Yu, Minghao Teng, Tao Zhou, Shunbo Li, Miao Lam, Tin Lun Chen, Fei T-Stone Robotics Institute The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Hong Kong Hong Kong Center for Logistics Robotics Hong Kong Computing Technologies Co. Ltd. Shenzhen China Institute of Technological Sciences Wuhan University Wuhan China School of Science and Engineering The Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781665481090

One of the grand goals in robotics is to develop a versatile robot capable of executing a wide array of tasks based on language instructions. These tasks often involve long-horizon manipulation due to the complexity of the real-world tasks and the high-dimensional action space of the dual-arm mobile robots. This work proposes a generalizable framework that combines a Large Language Model, a Visual-language Model, and symbolic planning to address long-horizon bimanual mobile manipulation tasks. We use the Large Language Model as the commonsense reasoner to break down the task into a set of subgoals and generate goal-oriented state queries. Subsequently, we fine-tune a Visual-language Model to obtain answers to queries. Finally, we propose a Planning Domain Definition Language translator that translates the subgoal and the goal-oriented states into a symbolic planning problem that can be solved by search-based planners. The experiments show that the proposed method has generalization ability in novel objects and instruction. It outperforms the baseline methods across all the configurations. Moreover, our approach exhibits competence in increasingly complex tasks, encompassing those that demand upward of 10 planning steps. © 2024 IEEE.

关键词： Visual languages

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Artificial Neural Network Modeling for Predicting Thermal Conductivity of EG/Water-Based CNC Nanofluid for Engine Cooling Using Different Activation Functions

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Frontiers in Heat and Mass Transfer 2024年第2期22卷 537-556页

作者： Munirul Hasan Mustafizur Rahman Mohammad Saiful Islam Wong Hung Chan Yasser M.Alginahi Muhammad Nomani Kabir Suraya Abu Bakar Devarajan Ramasamy Faculty of Computing Universiti Malaysia Pahang Al-Sultan AbdullahPekanPahang26600Malaysia Faculty of Mechanical and Automotive Engineering Technology Universiti Malaysia Pahang Al-Sultan AbdullahPekanPahang26600Malaysia Department of Management and Information Technology St.Francis College179 Livingston StBrooklynNY11201USA Dell Technologies Data Analyticsand AutomationBukit TengahBukit Mertajam14000Malaysia Department of Computer Science Adrian CollegeAdrianMIUSA Department of Computer Science&Engineering United International University BangladeshUnited CityMadani AvenueBaddaDhaka1212Bangladesh

A vehicle engine cooling system is of utmost importance to ensure that the engine operates in a safe temperature *** most radiators that are used to cool an engine,water serves as a cooling *** performance of a radiator in terms of heat transmission is significantly influenced by the incorporation of nanoparticles into the cooling *** and uniformity of nanoparticle distribution are the two major factors for the practical use of *** shape and size of nanoparticles also have a great impact on the performance of heat *** researchers are investigating the impact of nanoparticles on heat *** study aims to develop an artificial neural network(ANN)model for predicting the thermal conductivity of an ethylene glycol(EG)/waterbased crystalline nanocellulose(CNC)nanofluid for cooling internal combustion *** implementation of an artificial neural network considering different activation functions in the hidden layer is made to find the bestmodel for the cooling of an engine using the *** of the model with different activation functions in artificial neural networks are analyzed for different nanofluid concentrations and *** artificial neural networks,Levenberg–Marquardt is an optimization approach used with activation functions,including Tansig and Logsig functions in the training *** findings of each training,testing,and validation phase are presented to demonstrate the network that provides the highest level of *** best result was obtained with Tansig,which has a correlation of 0.99903 and an error of 3.7959×10^(–8).It has also been noticed that the Logsig function can also be a good model due to its correlation of 0.99890 and an error of 4.9218×10^(–8).Thus ourANNwith Tansig and Logsig functions demonstrates a high correlation between the actual output and the predicted output.

关键词： Artificial neural network activation function thermal conductivity nanocellulose

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Investigation of the Accuracy of Thermographic Inspections of Photovoltaic Modules 29

Investigation of the Accuracy of Thermographic Inspections o...

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29th IEEE International Symposium for Design and Technology in Electronic Packaging, SIITME 2023

作者： Evstatiev, Boris Valov, Nikolay Gabrovska-Evstatieva, Katerina Mladenova, Tsvetelina Mihailov, Nicolay University of Ruse 'Angel Kanchev' Department of Electronics Ruse Bulgaria University of Ruse 'Angel Kanchev' Department of Automation and Mechatronics Ruse Bulgaria University of Ruse 'Angel Kanchev' Department of Computer Science Ruse Bulgaria University of Ruse 'Angel Kanchev' Department of Computing Ruse Bulgaria University of Ruse 'Angel Kanchev' Department of Electrical Power Engineering Ruse Bulgaria

ISBN: (纸本)9798350344110

Remote inspections of photovoltaic installations are an important factor for taking timely measures to increase their efficiency and reduce degradation. This study deals with the accuracy and uncertainty of thermal measurements of PV cells. An experiment is organized in order to compare the measured temperatures with means of contact sensor and contactless infrared cameras from different distance. The obtained results indicate significant difference in the measured peak temperatures with the different means. Furthermore, the temperature gradient of an affected cell depends strongly on the soiling area and could surpass 40°C, which is a precondition for significant errors in the measured temperatures, i.e. it creates a significant uncertainty. Another important observation is that for the investigated polycrystalline module no hotspot was created if 6% or less of a cell's area is covered. © 2023 IEEE.

关键词： Cells

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When Does Sora Show:The Beginning of TAO to Imaginative Intelligence and Scenarios engineering

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 809-815页

作者： Fei-Yue Wang Qinghai Miao Lingxi Li Qinghua Ni Xuan Li Juanjuan Li Lili Fan Yonglin Tian Qing-Long Han School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Department of Electrical and Computer Engineering Indiana University-Purdue University IndianapolisIndianapolisIN 46202USA Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.

关键词： something Intelligence replace

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Multiobjective Sequential Transfer Optimization: Benchmark Problems and Preliminary Results 13

Multiobjective Sequential Transfer Optimization: Benchmark P...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Xue, Xiaoming Feng, Liang Yang, Cuie Liu, Songbai Song, Linqi Tan, Kay Chen City University of Hong Kong Department of Computer Science Hong Kong College of Computer Science Chongqing University Chongqing China Northeastern University State Key Lab of Synthetic Automation for Process Industries Shenyang China College of Computer Science and Software Engineering Shenzhen University Shenzhen China The Hong Kong Polytechnic University Department of Computing Hong Kong

ISBN: (纸本)9798350308365

In cases of frequent problem-solving of multiobjective optimization tasks from a domain due to changing conditions or problem features, a growing number of individual tasks will be solved and stored in a database, providing an opportunity for a target task at hand to achieve better optimization performance through knowledge transfer from the previously-solved tasks, which is also known as sequential transfer optimization. Despite a variety of transfer algorithms that have been developed over the years, the research on the design of benchmark problems for evaluating such algorithms received far less attention. Oftentimes, the source and target tasks in existing test problems are manually assembled or extended from specific practical problems, limiting their ability to represent the diverse yet complex source-target similarity relationships in real-world problems. In light of this, we propose design methods to generate multiobjective sequential transfer optimization problems (MSTOPs) systematically in this work, wherein the Pareto manifolds of individual tasks and the manifold-based similarity between the tasks can be customized with ease, enabling a broad spectrum of representation of the diverse similarity relationships between the source-target Pareto manifolds of MSTOPs. Lastly, a benchmark suite with 12 test problems is developed using the proposed methods, which would serve as an arena for electing superior multiobjective sequential transfer optimization algorithms. The source code is available at https://***/XmingHsueh/MSTOP. © 2024 IEEE.

关键词： Optimization algorithms

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Reinforcement Learning-Based Optimal Control for Continuous-Time Quantized Systems via Adaptive Dynamic Programming

Reinforcement Learning-Based Optimal Control for Continuous-...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Omar Qasem Weinan Gao Omar R. Daoud Electrical and Computer Engineering Department School of Engineering and Computing American International University Al-Jahra Kuwait State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang Lianning China

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

Ahstract- This paper presents a comprehensive investigation into the stability analysis and design conditions for quantizers to ensure the closed-loop stability of continuous-time linear quantized systems, under the conditions derived by the small-gain theorem. The study begins by deriving explicit bounds on the quantizer parameters required for maintaining system stability. Building on this foundation, an optimal controller is designed using the linear quadratic regulator (LQR) framework, providing an efficient data-driven control strategy. To further enhance the system's performance, an adaptive dynamic programming (ADP) algorithm, referred to as the hybrid iteration (HI) method, is developed. This algorithm effectively learns the optimal control policy by leveraging the trajectories of the quantized states and inputs, thereby addressing the challenges posed by quantization constraints. The proposed HI approach combines the advantages of adaptive learning and optimization, making it well-suited for continuous-time systems with limited information. The simulation results confirm that the ADP approach with the provided conditions not only stabilizes the quantized system but also achieves optimal control performance under the specified quantization conditions. This study offers valuable insights and a robust methodological framework for addressing stability and control challenges, with insights to be expanded to continuous-time nonlinear quantized systems, with potential applications in various engineering domains, such as networked systems, robotics and autonomous systems.

关键词： Quantization (signal) Adaptive systems Regulators Simulation Heuristic algorithms Optimal control Stability analysis Dynamic programming Trajectory Thermal stability

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Health Data Analytics Using IoT: Transforming Healthcare Management and Treatment Strategies for Improved Patient Outcomes

Health Data Analytics Using IoT: Transforming Healthcare Man...

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2024 International Conference on Innovative computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Tuan, Dinh Cong Unnikrishnan, Paravthy Dhandayuthapani, Bala Vennila, M.E.M. Long, Choi Sang Sahoo, Deepali Rani Dai Nam University Faculty of Communication Viet Nam Amritapuri690525 India College of Computing and Information Sciences University of Technology and Applied Sciences Department of It Shinas Campus Oman Karpaga Vinayaga College of Engineering and Technology Department of Robotics and Automation Chengalpattu India Raffles University Faculty of Business Malaysia Symbiosis Law School Noida India Pune India

ISBN: (纸本)9798331543617

The integration of Web of Things (IoT) innovation within the healthcare segment has revolutionized conventional healthcare administration and treatment procedures, driving progressed quiet results. This paper looks at the transformative effect of well-being information analytics utilizing IoT in upgrading healthcare administrations, optimizing understanding care, and advancing preventive measures. The paper analyzes the key components and applications of IoT in healthcare, emphasizing its part in information collection, real-time observation, and examination of understanding imperative signs, action levels, and pharmaceutical adherence. With the help of IoT-enabled gadgets such as wearables, sensors, and keen checking frameworks, healthcare experts can assemble comprehensive, real-time persistent information, encouraging early discovery and opportune mediation for basic well-being issues. Besides, the utilization of IoT in well-being information analytics empowers the improvement of personalized treatment plans custom-fitted to a person's persistent needs, cultivating a patient-centric approach to healthcare conveyance. By leveraging machine learning calculations and prescient analytics, healthcare suppliers can expect potential well-being complications, in this manner minimizing the chance of antagonistic occasions and clinic readmissions. In addition, the execution of IoT-based healthcare arrangements advances further understanding and observing, empowering healthcare suppliers to offer ceaseless, personalized care past conventional healthcare settings. © 2024 IEEE.

关键词： Patient treatment

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Fuel Saving Effect and Performance of Velocity Control for Modern Combustion-Powered Scooters

arXiv

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arXiv 2023年

作者： Kreß, Jannis Rau, Jens Hebert, Hektor Perez-Peña, Fernando Schmidt, Karsten Morgado-Estévez, Arturo Department of Computing and Engineering Frankfurt University of Applied Sciences Hessen Frankfurt60318 Germany Department of Automation Electronics and Computing Architecture and Networks University of Cadiz Puerto Real Andalusia11519 Spain

This paper investigates the performance and fuel-saving effect of a velocity control algorithm on modern 50 cc scooters (Euro 5). The European Parliament has adopted major CO2 emission reductions by 2030. But modern combustion-powered scooters are inefficiently restricted and emit unnecessary amounts of CO2. Replacing the original restriction method with the system presented in this paper, the engine’s operating point is being improved significantly. Therefore, a Throttle-by-Wire-System senses the rider’s throttle command and manipulates the throttle valve. A redundant wheel speed sensor measures the precise vehicle velocity using the magneto-resistive principle. The entire system is managed by a central ECU, executing the actual velocity control, fail-safe functions, power supply and handling inputs/outputs. For velocity control, an adaptive PI-controller has been simulated, virtually tuned and implemented, limiting the max. velocity regulated by legal constraints (45 km/h). In this way, the environmentally harmful restrictors used today can be bypassed. By implementing a human-machine interface, including a virtual dashboard, the system is capable of interfacing with the rider. For evaluation purposes a measurement box has been developed, logging vehicle orientation, system/control variables and engine parameters. A Peugeot Kisbee 50 4T (Euro 5) is serving as test vehicle. Finally, the system has been evaluated regarding performance and fuel efficiency both through simulation and road testing. Fuel savings of 13.6 % in real-world test scenarios were achieved while maintaining vehicle performance. © 2023, CC BY.

关键词： Fuel economy

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Robust Object Recognition in Open Environments Based on Causal Inference

Robust Object Recognition in Open Environments Based on Caus...

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Robotics, Control and automation engineering (RCAE), International Conference on

作者： Ruonan Liu Shuai Wu Ping Kong Wei Xie Weidong Zhang Department of Automation Shanghai Jiao Tong University Shanghai China College of Intelligence and Computing Tianjin University Tianjin China School of Information and Communication Engineering Hainan University Hainan China Department of Automation Shanghai Jiaotong University Shanghai China

ISBN: (数字)9798350355642

ISBN: (纸本)9798350355659

The rapid development of artificial intelligence technology has drawn widespread attention to the problem of target recognition in open environments. Traditional target recognition methods are easily affected by environmental changes and interference noise, leading to insufficient recognition accuracy and robustness. This paper proposes a robust target recognition method based on causal inference, aiming to improve the robust performance of image recognition models in open environments. The method first extracts features from images, analyzes the impact of noise features such as the environment in image features, and derives the essential feature properties of the target. Then, the causal relationship is introduced into the target recognition, and by analyzing the relationship between the environment, the target, and the observation data, the features of the target are combined with the observation data to achieve accurate and stable recognition of the target. The proposed method has achieved good target recognition effects on multiple open datasets, and the experimental results show that the algorithm can effectively solve the problem of poor robustness of the target recognition model in open environments, providing strong support for practical applications. Through the application of this method, the stability and robustness of the target recognition model can be significantly improved, which has important practical application value.

关键词： Accuracy Image recognition automation Target recognition Noise Interference Feature extraction Robustness Stability analysis Robots

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An Overview of Advanced Gate Driver Concepts for SiC Semiconductors

An Overview of Advanced Gate Driver Concepts for SiC Semicon...

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International Conference on Electrical Drives and Power Electronics (EDPE)

作者： Tomislav Ivaniš Marinko Kovačić Department of Electric Machines Drives and Automation Unska 3 10000 Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

Silicon carbide (SiC) power transistors have been steadily gaining popularity in power electronics applications as they have improved properties over silicon based devices, namely silicon MOSFETs and IGBTs. However, because of very high switching speed which results in lower losses, in general application their use is often a concern because of electromagnetic interference (EMI). In order to fully utilise the potential of SiC based devices, a careful design of power stage, commutation loop and gate drive is needed. Because of this reason, this paper presents a review of existing gate drive methods for performance improvement of SiC devices. A special emphasis is given to the gate drive concepts, as it is an important element for the further advancement of SiC-based converters. With improved switching, specifically active gate driving techniques a compromise between EMI and switching losses can be achieved.

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