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Global Conference for Advancement in Technology (GCAT)

作者： S Ramkumar M Sridharan G Nareshbabu R Giri Kanagaraj Venusamy R Priyadharshini Department of Robotics and Automation Rajalakshmi Engineering College Thandalam Chennai India Department of Mechatronics Engineering Rajalakshmi Engineering College Thandalam Chennai India

Packaging is a crucial stage in the mass production of components, especially when it comes to threaded components fabrication. Currently, the process of segregating bolts based on their length and thread presence is done manually, leading to numerous errors during packaging. To address this issue and achieve greater accuracy and perfection, we propose a digital segregation method using an electronic control module. By placing this module along the assembly line, it can automatically divide bolts according to their lengths and the presence of threads, eliminating the need for manual intervention and reducing human errors. Implementing this mechatronics system allows for more precise and accurate punching of bolts based on their size, resulting in high-quality packaging that takes into account various segregation factors.

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Logarithmically Quantized Distributed Optimization over Dynamic Multi-Agent Networks

arXiv

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arXiv 2024年

作者： Doostmohammadian, Mohammadreza Pequito, Sérgio Mechatronics Department Faculty of Mechanical Engineering Semnan University Semnan Iran Department of Electrical and Computer Engineering Institute for Systems and Robotics Instituto Superior Técnico University of Lisbon Portugal

Distributed optimization finds many applications in machine learning, signal processing, and control systems. In these real-world applications, the constraints of communication networks, particularly limited bandwidth, necessitate implementing quantization techniques. In this paper, we propose distributed optimization dynamics over multi-agent networks subject to logarithmically quantized data transmission. Under this condition, data exchange benefits from representing smaller values with more bits and larger values with fewer bits. As compared to uniform quantization, this allows for higher precision in representing near-optimal values and more accuracy of the distributed optimization algorithm. The proposed optimization dynamics comprise a primary state variable converging to the optimizer and an auxiliary variable tracking the objective function's gradient. Our setting accommodates dynamic network topologies, resulting in a hybrid system requiring convergence analysis using matrix perturbation theory and eigenspectrumanalysis. © 2024, CC BY.

关键词： Support vector machines

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Real-Time Plant Recognition and Crop Row Navigation for Autonomous Precision Agricultural Sprayer Robot

Real-Time Plant Recognition and Crop Row Navigation for Auto...

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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Fazal Nasir Muhammad Haris Bilawal Khan Muhammad Tufail Muhammad Tahir Khan Zhang Dong Advanced Robotics and Automation Lab National Center of Robotics and Automation Peshawar Pakistan Department of Mechatronics Engineering University of Engineering and Technology Peshawar Pakistan Institute of Automation Qilu University of Technology (Shandong Academy of Sciences) Jinan China

This paper presents a vision-based selective spraying technique for an autonomous agricultural sprayer robot. In traditional methods, excessive chemical spraying cause deleterious effects on human health, environment and becomes uneconomical. In order to reduce the agrochemical wastage encounters in a broadcast spraying, a selective plant spraying method is used for crop chemical treatment. The sensor-based approach assisted with YOLOv7 model is deployed on a custom designed robot for recognizing and localizing the lettuce plants in field. The PID-based pressure controller is designed that minimizes the undesirable fluctuations cause by the opening/closing of solenoid-valve-nozzles (SVNs) during spraying. Thus the nozzle's spraying quality is maintained by keeping the pressure constant to a desired value. A visual servoing scheme for row tracking is presented that uses the detected plant's spatial features. The robustness of the visual-based navigation is validated in the real field experiments.

关键词： Service robots Plants (biology) Spraying Crops Wheels Robot sensing systems Visual servoing

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Low Power Coherent Ising Machine Based on Mechanical Kerr Nonlinearity

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Physical Review Letters 2023年第7期130卷 073802-073802页

作者： Yoonhyuk Rah Youngjae Jeong Sangyoon Han Kyoungsik Yu School of Electrical Engineering Korea Advanced Institute of Science and Technology KAIST Daejeon 34141 Republic of Korea Robotics and Mechatronics Engineering Daegu-Gyeongbuk Institute of Science and Technology DGIST Daegu 42988 Republic of Korea

Finding a reliable Ising machine for solving nondeterministic polynomial-class problems has attracted great attention in recent years, where an authentic system can be expanded with polynomial-scaled resources to find the ground state Ising Hamiltonian. In this Letter, we propose an extremely low power optomechanical coherent Ising machine based on a new enhanced symmetry breaking mechanism and highly nonlinear mechanical Kerr effect. The mechanical movement of an optomechanical actuator induced by the optical gradient force greatly increases the nonlinearity by a few orders and significantly reduces the power threshold using conventional structures capable of fabrication via photonic integrated circuit platforms. With the simple but strong bifurcation mechanism and remarkably low power requirement, our optomechanical spin model opens a path for chip-scale integration of large-size Ising machine implementations with great stability.

关键词： Kerr effect Nanophotonics Nonlinear optics

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Towards mechatronics Approach of System Design, Verification and Validation for Autonomous Vehicles

Towards Mechatronics Approach of System Design, Verification...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent mechatronics

作者： Chinmay Samak Tanmay Samak Venkat Krovi Department of Automotive Engineering Automation Robotics and Mechatronics Laboratory (ARMLab) Clemson University International Center for Automotive Research (CU-ICAR) Greenville USA

Modern-day autonomous vehicles are increasingly becoming complex multidisciplinary systems composed of mechanical, electrical, electronic, computing and information subsystems. Furthermore, the individual constituent technologies employed for developing autonomous vehicles have started maturing up to a point, where it seems beneficial to start looking at the synergistic integration of these components into sub-systems, systems, and potentially, system-of-systems. Hence, this work applies the principles of mechatronics approach of system design, verification and validation for the development of autonomous vehicles. Particularly, we discuss leveraging multidisciplinary co-design practices along with virtual, hybrid and physical prototyping and testing within a concurrent engineering framework to develop and validate a scaled autonomous vehicle using the AutoDRIVE Ecosystem. We also describe a case-study of autonomous parking application using a modular probabilistic framework to illustrate the benefits of the proposed approach.

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Terminal Sliding Modes-Based PLLs for Three-Phase Grid-Connected Inverters 49

Terminal Sliding Modes-Based PLLs for Three-Phase Grid-Conne...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Hosseinabadi, Pooyan Alinaghi Kermadi, Mostefa Pota, Hemanshu Mekhilef, Saad Abadi, Ali Soltani Sharif The School of Engineering and Information Technology The University of New South Wales CanberraACT Australia Kuala Lumpur Malaysia The School of Science Computing and Engineering Technologies Swinburne University of Technology HawthornVIC3122 Australia Institute of Automatic Control and Robotics Warsaw University of Technology Faculty of Mechatronics Warsaw Poland

ISBN: (纸本)9798350331820

This paper proposes and experimentally implements new phase-locked loop algorithms using non-adaptive and adaptive terminal sliding modes for the three-phase grid-connected inverters. The proposed algorithms aim to extract the grid voltage phase and frequency and provide them for the inverter controller. The proposed sliding mode-based PLL algorithms provide faster, more robust, and more accurate detection of the grid voltage information compared to the conventional PI-PLL. This leads to better current controller performance and subsequently, improves the quality of the injected currents into the grid. The finite-time stability notion is incorporated with robust sliding modes to ensure a fast convergence rate. An adaptive law is proposed to determine a proper value for the switching gain which leads to a better overall performance of the PLL compared with a non-adaptive one. The Lyapunov stability theory is used to obtain the stability proofs of the closed-loop systems under both designed sliding modes-based PLLs. The proposed PLL algorithms are validated by simulation and experimental results for the three-phase grid-connected inverter under normal and various abnormal grid conditions. © 2023 IEEE.

关键词： Phase locked loops

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Learning a Shape-Conditioned Agent for Purely Tactile In-Hand Manipulation of Various Objects

Learning a Shape-Conditioned Agent for Purely Tactile In-Han...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Johannes Pitz Lennart Röstel Leon Sievers Darius Burschka Berthold Bäuml Learning AI for Dextrous Robots Lab (***) Technical University of Munich Germany DLR Institute of Robotics & Mechatronics (German Aerospace Center) Machine Vision and Perception Group Technical University of Munich

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Reorienting diverse objects with a multi-fingered hand is a challenging task. Current methods in robotic in-hand manipulation are either object-specific or require permanent supervision of the object state from visual sensors. This is far from human capabilities and from what is needed in real-world applications. In this work, we address this gap by training shape-conditioned agents to reorient diverse objects in hand, relying purely on tactile feedback (via torque and position measurements of the fingers’ joints). To achieve this, we propose a learning framework that exploits shape information in a reinforcement learning policy and a learned state estimator. We find that representing 3D shapes by vectors from a fixed set of basis points to the shape’s surface, transformed by its predicted 3D pose, is especially helpful for learning dexterous in-hand manipulation. In simulation and real-world experiments, we show the reorientation of many objects with high success rates, on par with state-of-the-art results obtained with specialized single-object agents. Moreover, we show generalization to novel objects, achieving success rates of ~90% even for non-convex ***: https://***/manipulation/iros24

关键词： Training Visualization Three-dimensional displays Torque Shape Tactile sensors Reinforcement learning Position measurement Vectors Sensors

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A Convergent Approach of Mathematical Modelling and Deep Learning for Inverse Kinematics Solutions in Stewart Platform Parallel Robots

A Convergent Approach of Mathematical Modelling and Deep Lea...

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Machine Intelligence and Smart Innovation (ICMISI), International Conference on

作者： M. Elseiagy A. El-Sayed M. Elsamanty Mechatronics and Robotics Department Egypt Japan University of Science and Technology Computer Science and Engineering Department Egypt Japan University of Science and Technology Mechanical Department Faculty of Engineering Benha University

ISBN: (数字)9798350365740

ISBN: (纸本)9798350365757

The Stewart Platform, a sophisticated robotic mechanism known for its precision positioning and orientation in six degrees of freedom (6-DOF), is utilized as a testbed for the proposed solution. The unique design of the platform, combining translational and rotational movements, makes it suitable for applications that demand high accuracy and rapid position and orientation adjustments. It is widely used in sectors like flight simulators, animatronics, underwater research, and medical devices. This research presents an innovative solution for the inverse kinematics problem of the Stewart platform parallel robot by synergistically integrating mathematical modeling and deep learning techniques. The study introduces a fusion of fully connected neural networks and mathematical models, harnessing the computational prowess and adaptability of deep learning and the precision of established mathematical theories.

关键词： Deep learning Parallel robots Adaptation models Technological innovation Accuracy Computational modeling Neural networks

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Grasp planning and sign language gestures with 3D printed humanoid hand

Grasp planning and sign language gestures with 3D printed hu...

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International Scientific Conference Electronics (ET)

作者： Ivaylo Georgiev Valentin Nikolov Ivan Chavdarov Bozhidar Naydenov Bulgarian Academy of Sciences Acad. G. Bonchev St Bl. 1 Institute of Robotics Sofia Bulgaria Sensata Technologies Sofia Bulgaria Department of Mechatronics Robotics and Mechanics Faculty of Mathematics and Informatics University of Sofia “St. Kliment Ohridski” Sofia Bulgaria

ISBN: (数字)9798350376449

ISBN: (纸本)9798350376456

This article presents sign language gestures application used for control of humanoid 3D printed hand with fingers, based on a modular principle. The 3D printed fingers are designed to be manufactured assembled, which facilitates the construction of the hand. All actuators, sensors, and electronic components, used in the hand control, are located in the palm. The sign language application provides good opportunities to test the dexterity and mechanical limitations of the developed humanoid hand. In addition to the sign language gestures program, a second application is created that allows hand control based on user input for each finger. The implemented software programs are described. Functional experiments are conducted and discussed.

关键词： Wrist Sign language Three-dimensional displays Thumb Humanoid robots Prototypes Software Planning Windows Python

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Time of single-pulse TMS delivery during cognitive task affects subject’s reaction time 6

Time of single-pulse TMS delivery during cognitive task affe...

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6th International Conference "Neurotechnologies and Neurointerfaces", CNN 2024

作者： Udoratina, Anna Grigorev, Nikita Savosenkov, Andrey Ermolaev, Denis Maksimenko, Vladimir Gordleeva, Susanna Neurotechnology Department Lobachevsky State University of Nizhny Novgorod Nizhny Novgorod Russia ANO Neimark Nizhny Novgorod Russia Neurotechnology Department Lobachevsky State University of NizhnyNovgorod Nizhny Novgorod Russia Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Center for Neurotechnology and Machine Learning Immanuel Kant Baltic Federal University Kaliningrad Russia

ISBN: (纸本)9798350390926

In the present study, we investigated the effect of single-pulse TMS on sensorimotor integration (SI). Real and sham TMS was delivered while a subject performed a cognitive task to 6 areas of the cortex responsible for the motor component of SI, 200 ms or 800 ms after the presentation of visual stimuli. Here we show that the time of single-pulse TMS delivery affects the subject’s reaction time (RT). RT was significantly slower (p ©2024 IEEE.

关键词： Brain

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