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International Conference on Robotics and Artificial Intelligence (ICRAI)

作者： Muhammad Faiq Malik Haris Shahid Muhammad Haris Saleem Hassan Nazir Ahmed Nouman Mechatronics Engineering Department University of Engineering & Technology Taxila Pakistan Centre for Applied Autonomous Sensor Systems (AASS) Örebro University Örebro Sweden

Service robotics in dynamic environments is a challenging yet exciting field that has witnessed incredible advances in the last few decades. The credit for these advancements goes to artificial intelligence and robotics technological progressions. The housekeeping domain is an example of a service robotics domain. A high-level task planner can compute a plan of action, while low-level functionalities like perception and motion planning can ensure feasibility. We propose a solution to the housekeeping problem that utilizes the expressiveness of action language C+ to formalize actions and compute an action plan. To check for feasibility in the real world, we execute the action plans in a physics simulator, GAZEBO. We also propose benchmark instances for the housekeeping domain and evaluate our planning and execution times approach. We report possible execution failures for the benchmark instances and offer plausible solutions, such as hybrid planning, plan execution monitoring, and conditional planning.

关键词： Industries Automation Service robots Computational modeling Benchmark testing Planning Task analysis

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Gesture Recognition Model with Multi-Tracking Capture System for Human-Robot Interaction

Gesture Recognition Model with Multi-Tracking Capture System...

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2023 International Conference on System Science and Engineering, ICSSE 2023

作者： Nguyen, Khang H. V. Pham, Anh-Duy Minh, Tri Bien Phan, Thi Truc Thao Do, Xuan Phu Vietnamese-German University Mechatronics and Sensor Systems Technology Binh Duong Viet Nam Hochschule Bonn-Rhein-Sieg Department of Computer Science Sankt Augustin Germany Vienamese-German University Electrical and Computer Engineering Binh Duong Viet Nam Ho Chi Minh City Industry and Trade College Department of Mechanical Engineering Thu Duc Viet Nam

ISBN: (纸本)9798350322941

This study develops a wireless gesture recognition system for human-robot interaction using a high-speed marker-based motion capture system that requires no hardware development and no onboard power source. A novel gesture recognition model recognizes four gestures performed while holding a rigid-body object and translates them into robot control signals. The gestures are Flick Back to Front, Flick Front to Back, Rotate Clockwise, and Rotate Counter-clockwise. The system has four main components: a host PC with Vicon Tracker software, a set of Vicon Vantage V8 infrared cameras, a client PC that receives motion capture data and translates gestures to instruct a simulated KUKA youBot robot in the Gazebo simulation environment, and a gesture input unit. The poses of the gesture input unit are used to train the model using a surrogate deep neural network and the XGBoost ensemble method in a semi-supervised setting. The algorithm's decision-making process is explicated through the implementation of the Layer-wise Relevance Propagation methodology in PyTorch. The control approach is similar to the way trainers teach domestic pets to perform specific actions in response to different gestures. The proposed method offers an alternative to commanding the robot through typing or using joysticks. The current gesture recognition rate is around 60%, but performance will improve over time as new training samples are collected and event detection algorithms are improved to avoid misinterpreting unrelated movements as classified gestures. © 2023 IEEE.

关键词： Gesture recognition

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Editorial introduction for the special issue on sensors for microfluidic analysis systems

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IEEE sensors Journal 2008年第5期8卷 427-429页

作者： Nagle, H. Troy Fair, Richard B. Shannon, Mark A. Tan, Ooi Kiang Geschke, Oliver Ahn, Chong H. Kaynak, Okyay Vellekoop, Michael J. Duke University Department of Electrical and Computer Engineering Durham NC 27708 United States University of Illinois at Urbana-Champaign Department of Mechanical Engineering Urbana IL 61801-2906 United States Nanyang Technological University Division of Microelectronics School of Electrical and Electronic Engineering Singapore 639798 Singapore Technical University of Denmark Department of Micro- and Nanotechnology Kongens Lyngby DK-2800 Denmark University of Cincinnati Department of Electrical and Computer Engineering and Computer Science Cincinnati OH 45221-0030 United States Bogazici University Department of Electrical and Electronics Engineering Istanbul 34342 Turkey Vienna University of Technology Institute of Sensor and Actuator Systems Vienna A-1040 Austria Department of Electrical and Computer Engineering Duke University Electrochemical Society Department of Mechanical Engineering University of Illinois at Urbana-Champaign Urbana IL United States National Science Foundation Science and Technology Center WaterCAMPWS Micro-Nano-Mechanical Systems Laboratory Nanyang Technological University School of Electrical and Electronic Engineering Department of Electrical and Computer Engineering and Computer Science University of Cincinnati Cincinnati OH United States Departments of Electrical Engineering and Biomedical Engineering Microsystems and BioMEMS Laboratory Univensity of Cincinnati Departments of Electrical and Electronics Engineering Bogazici University Istanbul Turkey UNESCO Mechatronics Research and Annlication Centre Vienna Austria Department of Industrial Sensor Systems Institute of Sensor and Actuator Systems Vienna University of Technology Vienna Austria

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关键词： Special issues and sections sensor systems Microfluidics Microelectronics USA Councils Mechanical engineering Actuators Fabrication Biosensors Ferroelectric materials

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A New Novel of Prescribed Optimal Control and Its Application for Smart Damping System

A New Novel of Prescribed Optimal Control and Its Applicatio...

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International Conference on System Science and Engineering (ICSSE)

作者： Xuan Phu Do Thi Truc Thao Phan Khang H. V. Nguyen Mechatronics and Sensor Systems Technology Vietnamese German University Binh Duong Vietnam Department of Mechanical Engineering Ho Chi Minh city Industry and Trade College Thu Duc Vietnam

This study presents a new development of optimal control based on the prescribed performance model. The prescribed performance is analyzed following the boundaries of the system. The classical optimal control model is modified based on the Riccati-like equation for the upper and lower boundary functions of the prescribed model. To robust the proposed model, the new modifications of the Kalman function are suggested and then embedded in the optimal model. After formulating, the proposed control is applied in the smart suspension system under severe disturbance. The simulation results show that the proposed controller obtains the outstanding properties in control and guarantees the stability of the system

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Gesture Recognition Model with Multi-Tracking Capture System for Human-Robot Interaction

Gesture Recognition Model with Multi-Tracking Capture System...

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International Conference on System Science and Engineering (ICSSE)

作者： Khang H. V. Nguyen Anh-Duy Pham Tri Bien Minh Thi Truc Thao Phan Xuan Phu Do Mechatronics and Sensor Systems Technology Vietnamese-German University Binh Duong Vietnam Department of Computer Science Hochschule Bonn-Rhein-Sieg Sankt Augustin Germany Electrical and Computer Engineering Vienamese-German University Binh Duong Vietnam Department of Mechanical Engineering Ho Chi Minh city Industry and Trade College Thu Duc Vietnam

This study develops a wireless gesture recognition system for human-robot interaction using a high-speed marker-based motion capture system that requires no hardware development and no onboard power source. A novel gesture recognition model recognizes four gestures performed while holding a rigid-body object and translates them into robot control signals. The gestures are Flick Back to Front, Flick Front to Back, Rotate Clockwise, and Rotate Counter-clockwise. The system has four main components: a host PC with Vicon Tracker software, a set of Vicon Vantage V8 infrared cameras, a client PC that receives motion capture data and translates gestures to instruct a simulated KUKA youBot robot in the Gazebo simulation environment, and a gesture input unit. The poses of the gesture input unit are used to train the model using a surrogate deep neural network and the XGBoost ensemble method in a semi-supervised setting. The algorithm’s decision-making process is explicated through the implementation of the Layer-wise Relevance Propagation methodology in PyTorch. The control approach is similar to the way trainers teach domestic pets to perform specific actions in response to different gestures. The proposed method offers an alternative to commanding the robot through typing or using joysticks. The current gesture recognition rate is around 60%, but performance will improve over time as new training samples are collected and event detection algorithms are improved to avoid misinterpreting unrelated movements as classified gestures.

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Smart Maracas: An Innovative Triboelectric Nanogenerator for Earthquake Detection and Energy Harvesting

SSRN

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SSRN 2023年

作者： Chandrasekhar, Arunkumar Basith, Sayyid Abdul Vivekananthan, Venkateswaran Khandelwal, Gaurav Maria Joseph Raj, Nirmal Prashant Purusothaman, Yuvasree Kim, Sang Jae Nanosensors and Nanoenergy Lab Sensor Systems Lab Department of Sensor and Biomedical Technology School of Electronics Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India Center for Flexible Electronics Department of Electronics and Communication Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh 522302 India James Watt South Building School of Engineering University of Glasgow G12 8QQ United Kingdom Energy Harvesting Research Group School of Physics and Astronomy SUPA University of St Andrews United Kingdom Department of Materials Science and Engineering The Pennsylvania State University University ParkPennsylvania16802 United States Nanomaterials and Systems Laboratory Faculty of Applied Energy Systems Major in Mechatronics Engineering Jeju National University Korea Republic of Jeju National University Jeju63243 Korea Republic of

In an era marked by a growing demand for sustainable energy solutions and resilient disaster management systems, the convergence of innovative technologies holds the promise of addressing multifaceted challenges. This manuscript explores the multifunctional capabilities of the "smart maracas", a novel triboelectric nanogenerator (TENG) designed to harvest mechanical energy and simultaneously serve as an earthquake sensor. The smart maracas is a striking example of the potential of TENGs to harness mechanical motion for practical applications. The device converts mechanical energy into electrical power through meticulous engineering, opening avenues for self-sustaining power sources in various domains. The manuscript outlines the device's structural design, working principle, and real-time applications, spanning bio-mechanical energy harvesting, vibrational energy scavenging, rotational energy harvesting, and a unique sensing application for door monitoring. A pivotal aspect of this research revolves around the smart maracas' role as an earthquake sensor. Rigorous experiments were conducted to assess the device's responsiveness to simulated seismic forces. Notably, a linear relationship with an R² value of 0.9989 was established between the voltage generated by the smart maracas and seismic acceleration. This remarkable correlation underscores the device's precision and reliability in detecting seismic events, opening doors for cost-effective earthquake monitoring solutions. © 2023, The Authors. All rights reserved.

关键词： Earthquakes

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Influences of key factors on river water quality in urban and rural areas: A review

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Case Studies in Chemical and Environmental Engineering 2023年 8卷

作者： Anh, Nguyen Tuan Can, Le Duy Nhan, Nguyen Thi Schmalz, Britta Luu, Tran Le Doctoral Training Program in Sustainable Urban Development Vietnamese German University Viet Nam Nong Lam University of Ho Chi Minh City Gia Lai Campus Viet Nam Department of Mechatronics and Sensor Systems Technology Vietnamese German University Vanh Dai 4 Quarter 4 Thoi Hoa Ward Ben Cat Binh Duong Province Viet Nam Master Program in Water Technology Reuse and Management Vietnamese German University Vanh Dai 4 Quarter 4 Thoi Hoa Ward Ben Cat Binh Duong Province Viet Nam Chair of Engineering Hydrology and Water Management Technical University of Darmstadt Germany

Water quality in rivers is deteriorating in urban and rural areas due to natural and anthropogenic factors. Understanding how changes and factors affect river water quality is crucial for managing water quality in river basins. This review focuses on analyzing key factors affecting water quality, and the temporal and spatial variations of water quality in rivers flowing in rural and urban areas. Natural processes such as weathering of rocks, evapotranspiration, atmospheric deposition, climate change, and natural disasters cause changes in the quality of river water. Anthropogenic factors could stem from industrial effluents, domestic activities, and agricultural activities such as the application of fertilizers, manures, pesticides, animal husbandry activities, irrigation practices, deforestation, and aquaculture. The seasonal variations in river water quality are discussed, and land use or cover could affect water quality parameters in a negative or positive way. In addition to traditional contaminants such as biodegradable organic matter, heavy metals, and pathogens, emerging and persistent pollutants such as organochlorine pesticides (OCPs), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), perfluoroalkyl and polyfluoroalkyl substances (PFASs), and phamaceutic active compounds (PhACs) has been found in many rivers, which could pose a threat to human and animal health. The comparison of key factors and parameters in urban and rural areas is also clarified, which provides authorities and policymakers with a deep understanding and supports decision-making in sustainable water management. © 2023 The Authors

关键词： River basin River water quality Rural areas Urban areas Water pollution

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