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Optimization approach for a climbing robot with target tracking in WSNs

Journal of Ocean engineering and Science 2018年第4期3卷 282-287页

作者： Jerwin Prabu A Abhinav Tiwari Department of Robotics and Electronics Engineering Bharati Robotic SystemsIndia Department of Robotics and Mechanical Engineering Bharati Robotic SystemsIndia

Climbing robots are being developed for various *** confined space requires a compact locomotion system with vertical and overhead climbing *** achieve surface transition,Steering geometry Interaction system and static force are *** ubiquitous infrastructure and excellent coverage,they can be used for providing location information for various location-based services,especially in indoor *** structure is designed for a magnetic wall-climbing robot to gradually decrease the magnetic force when it is transiting between perpendicular magnetic *** paper describes the design process of a magnetic wall climbing robot,which adopts SgI and has the potential to carry materials in a confined space with an energy efficient system *** resolve the problem of target tracking,it is essential to deploy a system *** the last two decades,several researchers have recommended many remote user authentication *** are continuously trying to enhance the security in material handling automation system by introducing several features into their work.A working prototype has been built based on the optimized dimension.

关键词： Climbing Robot Surface transition Wireless Sensor Networks(WSNs) Target Tracking Static Force Steering Geometry Interaction(SgI).

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Cu@Nc as High-Performance and Durable Electrocatalyst for Oxygen Reduction Reaction in Alkaline Membrane Fuel Cells

SSRN

引用

SSRN 2022年

作者： Peera, Shaik Gouse Liu, Chao Asokan, Arunchander Suss, Matthew E. Department of Environmental Science Keimyung University 1095 Dalseo-gu Daegu42601 Korea Republic of Faculty of Materials Metallurgy and Chemistry Jiangxi University of Science and Technology Ganzhou341000 China Faculty of Mechanical Engineering Technion – Israel Institute of Technology Haifa320003 Israel Grand Technion Energy Program Technion – Israel Institute of Technology Haifa3200003 Israel Wolfson Department of Chemical Engineering Technion – Israel Institute of Technology Haifa3200003 Israel

Discovery of electrocatalysts composed of cheap transition metals are in urgent to replace the traditional Pt/C catalyst used for oxygen reduction reaction (ORR). Herein, we synthesized Cu nanoparticles encapsulated with nitrogen-doped carbon (Cu@NC) as an excellent and durable catalyst for ORR. A systematic evaluation of effect of Cu content, acid leaching and secondary heat treatment have been established with the help of half-cell studies. The morphological analysis revealed that Cu nanoparticles surrounded by a thick nitrogen doped carbon layers and further, the acid leaching and subsequent pyrolysis, boosted the electrocatalytic performance. The optimized Cu@NC catalyst showed onset potential and half-wave potential of 0.975 V vs. RHE (potential corresponding to a current density of 0.1 mA cm-2) and 0.85 V vs. RHE, surpassing Pt/C catalyst. In addition, the Cu@NC catalyst exhibited outstanding durability, tolerance to carbon monoxide and methanol molecules. In the alkaline fuel cell, Cu@NC catalyst delivered 118 mW cm-2 peak power density in alkaline fuel cell operated with H2-O2, whereas Pt/C only delivered a peak power density of 97 mW cm-2 under ambient operating conditions. High ORR activity and better stability of Cu@NC catalyst could be a potential alternative to Pt/C catalyst in alkaline fuel cells and metal-air cell cathodes. © 2022, The Authors. All rights reserved.

关键词： Electrolytic reduction

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Implementing Reactivity in Molecular Dynamics Simulations with Harmonic Force Fields

arXiv

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arXiv 2021年

作者： Winetrout, Jordan J. Kanhaiya, Krishan Kemppainen, Joshua in‘t Veld, Pieter J. Sachdeva, Geeta Pandey, Ravindra Damirchi, Behzad van Duin, Adri Odegard, Gregory M. Heinz, Hendrik Department of Chemical and Biological Engineering University of Colorado at Boulder BoulderCO80309 United States Materials Science and Engineering Program University of Colorado at Boulder BoulderCO80309 United States Insitute of Physics Ruhr University Bochum Universitätstrasse 150 Bochum44801 Germany Department of Mechanical Engineering - Engineering Mechanics Michigan Technological University HoughtonMI49931 United States BASF SE Ludwigshafen67056 Germany Department of Physics Michigan Technological University HoughtonMI49931 United States Department of Mechanical Engineering Pennsylvania State University University ParkPA16802 United States

The simulation of chemical reactions and mechanical properties including failure from atoms to the micrometer scale remains a longstanding challenge in chemistry and materials science. Bottlenecks include computational feasibility, reliability, and cost. We introduce a method for reactive molecular dynamics simulations using a clean replacement of non-reactive classical harmonic bond potentials with reactive, energy-conserving Morse potentials, called the Reactive INTERFACE Force Field (IFF-R). IFF-R is compatible with force fields for organic and inorganic compounds such as IFF, CHARMM, PCFF, OPLS-AA, and AMBER. Bond dissociation is enabled by three interpretable Morse parameters per bond type and zero energy upon disconnect. Use cases for bond breaking in molecules, failure of polymers, carbon nanostructures, proteins, composite materials, and metals are shown. The simulation of bond forming reactions was included via template-based methods. IFF-R maintains the accuracy of the corresponding nonreactive force fields and is about 30 times faster than prior reactive simulation methods. © 2021, CC BY-NC-ND.

关键词： Molecular dynamics

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Feature-Fused Deep Learning Approach for Hand Gesture Recognition in Intelligent Myoelectric Hand

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IEEE Sensors Journal 2025年

作者： Yan, Lingyun Bi, Luzheng Zhang, Zhihong Wei, Yuyang Xiu, Haohua Shanghai Institute of Technology School of Electrical and Electronic Engineering Shanghai201418 China Beijing Institute of Technology School of Mechanical Engineering Beijing100811 China University of Oxford Department of Engineering Science OxfordOX1 3PJ United Kingdom Jilin University Key Laboratory of Bionic Engineering Ministry of Education Changchun130022 China Ningbo University of Technology Robotics Institute of NBUT Ningbo315211 China

Accurate and efficient hand gesture recognition is a cornerstone for advancing the functionality of myoelectric prostheses, enabling intuitive and responsive human-machine interaction. In this study, we present a novel hybrid deep learning architecture that synergistically integrates convolutional neural networks (CNNs) with Transformer models to achieve unprecedented accuracy in electromyogram (EMG)-based hand gesture classification. By leveraging advanced feature engineering, we extract and combine time-domain, frequency-domain, and time-frequency features to provide a comprehensive representation of muscle activity patterns. This approach addresses critical challenges in existing methods, such as poor generalization and limited robustness to subject variability. The proposed system achieves a state-of-the-art recognition accuracy of 98.5% and an F1-score of 0.98 across 12 distinct hand gestures, surpassing existing methodologies. Additionally, we validate the practicality of our system by implementing it in a real-time control platform for a myoelectric hand, demonstrating its capability to perform precise, real-world motor tasks. Our findings represent a significant step forward in neural systems and rehabilitation engineering, offering a transformative solution for enhancing the usability and functionality of intelligent myoelectric prostheses. © 2001-2012 IEEE.

关键词： Myoelectrically controlled prosthetics

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Cooperative collision avoidance control of robotic fish propelled by a servo/ipmc driven hybrid tail

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ASME 2019 Dynamic Systems and Control Conference, DSCC 2019

作者： Yi, Xiongfeng Chen, Zheng Chakravarthy, Animesh Bio-inspired Robotics and Controls Lab Department of Mechanical and Engineering University of Houston HoustonTX77204 United States Department of Mechanical and Aerospace Engineering University of Texas at Arlington ArlingtonTX76019 United States

ISBN: (纸本)9780791859162

This paper develops and demonstrates cooperative collision avoidance control on two robotic fish propelled by a servo motor and an ionic polymer-metal composite (IPMC)-driven fish tail. First, experiments conducted on a servo motor/IPMC-driven fish demonstrate an impulsive turning behavior in the fish's trajectory under the application of a specific frequency, amplitude of the servo motor, and a constant voltage on the IPMC joint. These experiments validate the 'back relaxation' of the IPMC joint by observing the angular velocity and the centripetal acceleration of the fish. This impulsive turning speed due to the 'back relaxation' of IPMC joint is subsequently modeled by a transfer function and this transfer function is then integrated into the development of the collision avoidance laws for the fish. The collision avoidance control law utilizes the impulsive turning capability of the robotic fish. An experimental validation of the collision avoidance law is performed. © 2019 ASME.

关键词： Transfer functions

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Relational graph learning on visual and kinematics embeddings for accurate gesture recognition in robotic surgery

arXiv

引用

arXiv 2020年

作者： Long, Yonghao Wu, Jie Ying Lu, Bo Jin, Yueming Unberath, Mathias Liu, Yun-Hui Heng, Pheng Ann Dou, Qi The Department of Computer Science and Engineering The Chinese University of Hong Kong The T Stone Robotics Institute CUHK The T Stone Robotics Institute The Department of Mechanical and Automation Engineering The Chinese University of Hong Kong The Department of Computer Science Johns Hopkins University

Automatic surgical gesture recognition is fundamentally important to enable intelligent cognitive assistance in robotic surgery. With recent advancement in robot-assisted minimally invasive surgery, rich information including surgical videos and robotic kinematics can be recorded, which provide complementary knowledge for understanding surgical gestures. However, existing methods either solely adopt uni-modal data or directly concatenate multi-modal representations, which can not sufficiently exploit the informative correlations inherent in visual and kinematics data to boost gesture recognition accuracies. In this regard, we propose a novel online approach of multi-modal relational graph network (i.e., MRG-Net) to dynamically integrate visual and kinematics information through interactive message propagation in the latent feature space. In specific, we first extract embeddings from video and kinematics sequences with temporal convolutional networks and LSTM units. Next, we identify multi-relations in these multi-modal embeddings and leverage them through a hierarchical relational graph learning module. The effectiveness of our method is demonstrated with state-of-the-art results on the public JIGSAWS dataset, outperforming current uni-modal and multi-modal methods on both suturing and knot typing tasks. Furthermore, we validated our method on in-house visual-kinematics datasets collected with da Vinci Research Kit (dVRK) platforms in two centers, with consistent promising performance achieved. Our code and data are released at: https://***/~yhlong/***. Copyright © 2020, The Authors. All rights reserved.

关键词： Kinematics

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Geometry and thickness dependant anomalous mechanical behavior of fabricated SU-8 thin film micro-cantilevers

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Journal of Micromanufacturing 2020年第2期3卷 113 - 120页

作者： Aviru Kumar Basu Anup Basak Shantanu Bhattacharya Design Program Indian Institute of Technology Kanpur Uttar Pradesh IndiaMicrosystems Fabrication Laboratory Department of Mechanical Engineering Indian Institute of Technology Kanpur Uttar Pradesh India Department of Mechanical Engineering Indian Institute of Technology Tirupati Andhra Pradesh India

SU-8 micro-cantilever arrays consisting of V- and M-shaped structures fabricated using a simplified single hard mask step. Bending tests were performed under similar peak loads (ranging 2–10 µN), with thickness ranging between micron (3.5 µm) and sub-micron (0.2 µm) scales. Various mechanical properties such as stiffness and hysteresis are determined from the load versus deflection curves. When the thickness of the V-shaped beam is decreased from 2 µm to 0.2 µm, the stiffness increases by a factor of 2.7, which is in contradiction with the classical beam theory according to which the stiffness for 0.2 µm beam should be three orders of magnitude less than that of 2 µm beam. Micropolar elasticity theory with a variable-intrinsic length scale (thickness dependant) is used to explain such an anomalous response. Experimentally obtained stiffness of two M-shaped beams of thickness 2 µm and 0.2 µm are almost identical. Reason behind this contradictory result is that the thicker beam has a residual strain with a large plastic deformation which usually increases the cross-linking network density, leading to increase in elastic modulus, hardness and thus stiffness of polymers. But the thinner beam has undergone an elastic deformation. The size effect of V- and M-shaped cantilever beams is discussed.

关键词： Cantilever micropolar elasticity intrinsic length scale size effect

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A critical evaluation on design and development of smart dust sensor for mechatronics applications

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AIP Conference Proceedings 2023年第1期2690卷

作者： Christu Paul Ramaian Nadanakumar Vinayagam Kuppan Chetty Ramanathan Joshuva Arockia Dhanraj Nandakumar Selvaraju Jenoris Muthiya Solomon Shridhar Anaimuthu 1Centre for Automation and Robotics (ANRO) Department of Mechanical Engineering Hindustan Institute of Technology and Science Padur Chennai 603103 India 2Department of Automobile Engineering Hindustan Institute of Technology and Science Padur Chennai 603103 India 3Department of Automobile Engineering Dayananda Sagar College of Engineering Bengaluru Karnataka 560078 India 4Department of Automobile Engineering KCG College of Technology Chennai 600117 India

In the advanced world that we have today, it is important for consumers to have devices that are smaller in size and are easily available, and should be powerful in terms of specifications and performance. Also, there is a demand for the industries to miniaturize the parts as smaller as possible in order to meet the consumer requirements. A sensor is a key element in any automated system/device as it senses the physical changes in the environment and processes this data. Thus, paving way for smart sensors which have revolutionized the tech industry by their ability to consist an entire data conversion and processing units on a single chip or the System on Chip (SoC). The presented review paper describes about the research survey performed on sensors, transducers, and also on the evolving smart sensor technology which helped in innovating the state-of-the-art sensor technology such as the smart dust. A detailed study on the smart dust sensor technology and its capabilities to sense physical phenomena such as sound, vibration, temperature, light, magnetism, acceleration, position, stress, humidity, and chemical traces has been analyzed. At present, the smart dust sensor technology is under critical research, testing, and prototyping process. Furthermore, the future scope of the smart dust or mote technology is discussed by the describing the need for these sensors in various fields and also by showing the graphical representation of the Gartner’s hype cycle. The paper concludes by presenting the important aspects of a smart dust sensor, its usability, necessity, and also estimating the impact of this sensor technology in the rapid advancement of the tech industry.

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Phase Stability of Hexagonal/cubic Boron Nitride Nanocomposites

arXiv

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arXiv 2023年

作者： Biswas, Abhijit Xu, Rui Christiansen-Salameh, Joyce Jeong, Eugene Alvarez, Gustavo A. Li, Chenxi Puthirath, Anand B. Gao, Bin Garg, Arushi Gray, Tia Kannan, Harikishan Zhang, Xiang Elkins, Jacob Pieshkov, Tymofii S. Vajtai, Robert Glen Birdwell, A. Neupane, Mahesh R. Pate, Bradford B. Ivanov, Tony Garratt, Elias J. Dai, Pengcheng Zhu, Hanyu Tian, Zhiting Ajayan, Pulickel M. Department of Materials Science and Nanoengineering Rice University HoustonTX77005 United States Sibley School of Mechanical and Aerospace Engineering Cornell University IthacaNY14853 United States Department of Physics and Astronomy Rice University HoustonTX77005 United States Department of Materials Science and Engineering Indian Institute of Technology Kanpur Kanpur208016 India Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States DEVCOM Army Research Laboratory RF Devices and Circuits AdelphiMD20783 United States Naval Research Laboratory WashingtonDC20375 United States

Boron nitride (BN) is an exceptional material and among its polymorphs, two-dimensional (2D) hexagonal and three-dimensional (3D) cubic BN (h-BN and c-BN) phases are most common. The phase stability regimes of these BN phases are still under debate and phase transformations of h-BN/c-BN remain a topic of interest. Here, we investigate the phase stability of 2D/3D h-BN/c-BN nanocomposites and show that the co-existence of two phases can lead to strong non-linear optical properties and low thermal conductivity at room temperature. Furthermore, spark-plasma sintering of the nanocomposite shows complete phase transformation to 2D h-BN with improved crystalline quality, where 3D c-BN grain sizes governs the nucleation and growth kinetics. Our demonstration might be insightful in phase engineering of BN polymorphs based nanocomposites with desirable properties for optoelectronics and thermal energy management applications. © 2023, CC BY.

关键词： Nanocomposites

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Correction to: A Review on the Force Sensing and Force Feedback-Based Navigation of Mobile Robots (International Journal of Precision engineering and Manufacturing, (2025), 10.1007/s12541-025-01244-3)

引用

International Journal of Precision engineering and Manufacturing 2025年第5期26卷 1313-1313页

作者： Lee, Woojae Joo, Hyungchan Kang, Yoon-Koo Seo, TaeWon Department of Mechanical Convergence Engineering Hanyang University Wangsimni-ro Seongdong-gu Seoul04763 Korea Republic of Robot Development Team HD HYUNDAI ROBOTICS Bundangsuseo-ro 477 Seongnam-si Gyeonggi-do13553 Korea Republic of

In the original version of this article, a note in the Author Information section has been omitted by mistake. The missing note is as follows: "This paper is an invited paper (Invited Review)" The original version of this article has been corrected. © The Author(s), under exclusive licence to Korean Society for Precision engineering 2025.

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