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Multi-Robot Scan-n-Print for Wire Arc Additive Manufacturing

ASME Letters in Translational robotics 2025年第1期1卷 011003页

作者： Lu, Chen-Lung He, Honglu Ren, Jinhan Dhar, Joni Saunders, Glenn Julius, Agung Samuel, Johnson Wen, John T. https://***/01rtyzb94Rensselaer Polytechnic Institute Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY 12180 Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY 12180 https://***/01rtyzb94Rensselaer Polytechnic Institute Department of Mechanical Aerospace and Nuclear Engineering Rensselaer Polytechnic Institute Troy NY 12180 https://***/01rtyzb94Rensselaer Polytechnic Institute Manufacturing Innovation Center Rensselaer Polytechnic Institute Troy NY 12180 Department of Mechanical Aerospace and Nuclear Engineering Rensselaer Polytechnic Institute Troy NY 12180

Robotic Wire Arc Additive Manufacturing (WAAM) is a metal additive manufacturing technology offering flexible 3D printing while ensuring high-quality near-net-shape final parts. However, WAAM also suffers from geometric imprecision, especially for low-melting-point metals such as aluminum alloys. In this article, we present a multi-robot framework for WAAM process monitoring and control. We consider a three-robot setup: a 6-DoF welding robot, a 2-DoF trunnion platform, and a 6-DoF sensing robot with a wrist-mounted laser line scanner measuring the printed part height profile. The welding parameters, including the wire feed rate, are held constant based on the materials used, so the control input is the robot path speed. The measured output is the part height profile. The planning phase decomposes the target shape into slices of uniform height. During runtime, the sensing robot scans each printed layer, and the robot path speed for the next layer is adjusted based on the deviation from the desired profile. The adjustment is based on an identified model correlating the path speed to changes in height. The control architecture coordinates the synchronous motion and data acquisition between all robots and sensors. Using a three-robot WAAM testbed, we demonstrate significant improvements of the closed-loop scan-n-print approach over the current open loop result on both a flat wall and a more complex turbine blade shape.

关键词： welding process control multiple robot scan-n-print welding robot WAAM

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Design of QoS Aware Routing Protocol for IoT Assisted Clustered WSN

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computers, Materials & Continua 2022年第5期71卷 3785-3801页

作者： Ashit Kumar Dutta S.Srinivasan Bobbili Prasada Rao B.Hemalatha Irina V.Pustokhina Denis A.Pustokhin Gyanendra Prasad Joshi Department of Computer Science and Information Systems College of Applied SciencesAlmaarefa UniversityRiyadh13713Kingdom of Saudi Arabia Saveetha School of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha NagarThandalamChennai602105India Department of Electrical and Electronics Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Electronics and Communication Engineering Thirumalai Engineering CollegeKancheepuram631551India Department of Entrepreneurship and Logistics Plekhanov Russian University of Economics117997MoscowRussia Department of Logistics State University of Management109542MoscowRussia Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea

In current days,the domain of Internet of Things(IoT)and Wireless Sensor Networks(WSN)are combined for enhancing the sensor related data transmission in the forthcoming networking *** and routing techniques are treated as the effective methods highly used to attain reduced energy consumption and lengthen the lifetime of the WSN assisted IoT *** this view,this paper presents an Ensemble of Metaheuristic Optimization based QoS aware Clustering with Multihop Routing(EMOQoSCMR)Protocol for IoT assisted *** proposed EMO-QoSCMR protocol aims to achieve QoS parameters such as energy,throughput,delay,and *** proposed model involves two stage processes namely clustering and ***,the EMO-QoSCMR protocol involves crossentropy rain optimization algorithm based clustering(CEROAC)technique to select an optimal set of cluster heads(CHs)and construct ***,oppositional chaos game optimization based routing(OCGOR)technique is employed for the optimal set of routes in the IoT assisted *** proposed model derives a fitness function based on the parameters involved in the IoT nodes such as residual energy,distance to sink node,*** proposed EMOQoSCMR technique has resulted to an enhanced NAN of 64 nodes whereas the LEACH,PSO-ECHS,E-OEERP,and iCSHS methods have resulted in a lesser NAN of 2,10,42,and 51 *** performance of the presented protocol has been evaluated interms of energy efficiency and network lifetime.

关键词： Internet of things wireless sensor networks clustering routing metaheuristics cluster head selection QoS parameters

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Interactions Between Wind Turbines and Synchronous Condensers Equipped with Flywheels

Interactions Between Wind Turbines and Synchronous Condenser...

引用

IEEE Electronic Power Grid (eGrid)

作者： Lawrence Hiquiana Jian Sun John Schmall Scott Zuloaga Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA Electrical Reliability Council of Texas (ERCOT) Taylor TX USA

ISBN: (数字)9798331505493

ISBN: (纸本)9798331505509

Synchronous condensers integrated with a flywheel can be used to enhance system inertia in addition to providing voltage and reactive power support. The added flywheel introduces torsional modes that may interact with the rest of the system in ways like what has been studied for synchronous generators. This paper shows how such interactions may play out in wind power systems. The focus will be 1) torque amplification when a torsional mode is excited by an existing electrical resonance and 2) torsional control interaction when the torsional mode creates a variation in the synchronous condenser’s impedance and forms an unstable oscillation with a nearby wind turbine. Modeling and analysis are performed in the frequency-domain using impedance-based methods and verified by EMT simulation.

关键词： Reactive power Torque Rotors Wind power generation Resonance Synchronous generators Stability analysis Flywheels Wind turbines Oscillators

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Enhancing Precision Agriculture Through Human-in-the-Loop Planning and Control

Enhancing Precision Agriculture Through Human-in-the-Loop Pl...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Shankar A. Deka Sujet Phodapol Andreu Matoses Gimenez Victor Nan Fernandez-Ayala Rufus Wong Pian Yu Xiao Tan Dimos V. Dimarogonas Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Division of Decision and Control Systems School of EECS Royal Institute of Technology (KTH) Stockholm Sweden Department of Cognitive Robotics Faculty of Mechanical Engineering TU Delft Delft Netherlands Department of Computer Science University of Oxford Oxford UK

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In this paper, we introduce a ROS based framework designed for the planning and control of robotic systems within the context of precision agriculture, with an emphasis on human-in-the-loop capabilities. Utilizing Linear Temporal Logic to articulate complex task specifications, our algorithm creates high-level robotic plans that are not only correct by design but also adaptable in real time by human operators. This dual-focus approach ensures that while humans have the flexibility to modify the high-level plan on-the-fly or even take over low-level control of the robots, the system inherently safeguards against any human actions that could potentially breach the predefined task specifications. We demonstrate our algorithm within the dynamic and challenging environment of a real vineyard, where the collaboration between human workers and robots is critical for tasks such as harvesting and pruning, and show the practical applicability and robustness of our software. This work marks a pioneering application of formal methods to complex, real-world agricultural environments.

关键词： Precision agriculture Heuristic algorithms Software algorithms Robustness Human in the loop Software Real-time systems Planning Robots Multi-agent systems

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Error-correcting Codes in Communication systems

Error-correcting Codes in Communication Systems

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Khawla Almazrouei Khawla A Alnajjar Department of Computer Engineering University of Sharjah Sharjah UAE Autonomous Robotics Research Centre Technology Innovation Institute Abu Dhabi UAE Department of Electrical Engineering University of Sharjah Sharjah UAE

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

In most communication systems, when transmitting or receiving a signal, some unwanted signals may get introduced into the communications, making the quality of the communication poor. This disturbance, referred to as noise, can affect the reliability and quality of a digital communication system by corrupting or getting a message scrambled whenever it is transmitted. To prevent these errors, error-correction codes help detect and correct these errors arising during data transmission within digital communication systems. In communication systems, such error-correcting codes are essential for ensuring the efficient and reliable exchange of information over noisy channels like satellite links, optical fibers, and wireless networks. As such, the work presented in this paper delves into the issue of noisy data in communication systems and how error-correcting codes can be used to solve the problem. To achieve this, a review of different relevant literature by various scholars is done to present authentic and verifiable data on error-correcting codes for communication systems. On top of that, this paper introduces a novel approach by integrating advanced machine learning techniques, particularly artificial neural networks, to enhance the effectiveness and adaptability of error-correcting codes in diverse and dynamically changing communication environments, significantly surpassing traditional error correction methods.

关键词： Satellites Reviews Wireless networks Noise Machine learning Digital communication Error correction codes

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Two-Stage Representation Refinement Based on Convex Combination for 3-D Human Poses Estimation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6500-6508页

作者： Chen, Luefeng Cao, Wei Zheng, Biao Wu, Min Pedrycz, Witold Hirota, Kaoru China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Macau University of Science and Technology Institute of Systems Engineering Taipa999078 China Istinye University Research Center of Performance and Productivity Analysis Istanbul34010 Turkey Tokyo Institute of Technology Yokohama226-8502 Japan

In the human pose estimation task, on the one hand, 3-D pose always has difficulty in dividing different 2-D poses if the view is limited;on the other hand, it is hard to reduce the lifting ambiguity because of the lack of depth information, it is an important and challenging problem. Therefore, two-stage representation refinement based on the convex combination for 3-D human pose estimation is proposed, in which the two-stage method includes a dense-spatial-temporal convolutional network and a local-to-refine network. The former is applied to determine the features between each video frame;the latter is used to get the different scales of pose details. It aims to address the difficulty of estimating 3-D human pose from 2-D image sequences. In such a way, it can better use the relations between every frame in the sequence of the pose video to produce more accurate results. Finally, we combine the above network with a block called convex combination to help refine the 3-D pose location. We test the proposed approach on both Human3.6m and MPII datasets. The result confirms that our method can achieve better performance than improved CNN supervision, a simple yet effective baseline, and coarse-to-fine volumetric prediction. Besides, a robustness test experiment is carried out for the proposed method while the input is interrupted. The result verifies that our method shows better robustness. © 2024 IEEE.

关键词： Convolution

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Fingertip Ultrasonic Array for Tactile Rendering

Fingertip Ultrasonic Array for Tactile Rendering

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Jace Rozsa Sarah Costrell Melisa Orta Martinez Gary K. Fedder Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh USA Department of Mechanical Engineering Carnegie Mellon University Pittsburgh USA Robotics Institute Carnegie Mellon University Pittsburgh USA

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

A miniature haptic stimulation device utilizes focused ultrasound to deliver a tactile haptic sensation to the finger. The 1-3 piezocomposite device has a 1 cm 2 footprint, which is an order of magnitude smaller than other ultrasonic haptic devices and is a good candidate for wearable tactile rendering systems. The device focuses energy to a 1 mm 3 voxel. The current prototype was validated with a small, preliminary human subject study and requires an average input voltage of 68.8 V to elicit tactile sensation. The sensory drive voltage threshold will decrease with future refinement of mechanical impedance matching and focusing.

关键词： Ultrasonic imaging Focusing Prototypes High-voltage techniques Rendering (computer graphics) Robot sensing systems Acoustics

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Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces 38

Taming "data-hungry" reinforcement learning? Stability in co...

引用

38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Duan, Yaqi Wainwright, Martin J. Department of Technology Operations and Statistics Stern School of Business New York University New YorkNY10012 United States Laboratory for Information and Decision Systems Statistics and Data Science Center Department of Electrical Engineering and Computer Science Department of Mathematics Massachusetts Institute of Technology CambridgeMA02139 United States

We introduce a novel framework for analyzing reinforcement learning (RL) in continuous state-action spaces, and use it to prove fast rates of convergence in both off-line and on-line settings. Our analysis highlights two key stability properties, relating to how changes in value functions and/or policies affect the Bellman operator and occupation measures. We argue that these properties are satisfied in many continuous state-action Markov decision processes. Our analysis also offers fresh perspectives on the roles of pessimism and optimism in off-line and on-line RL. © 2024 Neural information processing systems foundation. All rights reserved.

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High-Lift Prediction Workshop 5: High-Order Discretization Technology Focus Group Summary

High-Lift Prediction Workshop 5: High-Order Discretization T...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Galbraith, Marshall C. Ruiz-Gironés, Eloi Roca, Xevi Wang, Z.J. Holst, Kevin R. Skaperdas, Vangelis Department of Aeronautics and Astronautics Massachusetts Institute of Technology CambridgeMA02139 United States Applications in Science and Engineering Barcelona Supercomputing Center - BSC Barcelona Spain Department of Aerospace Engineering University of Kansas LawrenceKS66045 United States Electrical Engineering and Computer Science University of Tennessee KnoxvilleTN37996 United States Customer Service BETA CAE Systems Thessaloniki Greece

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This paper summarizes the High-Order Technical Focus Group (HO-TFG) submissions forthe 5th AIAA High-Lift Prediction Workshop (HLPW-5). The goal of the workshop was to assess the state-of-the-art in mesh generation and computational fluid dynamics software for predicting peak lift of transport aircraft with flaps and slats deployed. Numerous geometric build ups of the Common Research Model High-Lift (CRM-HL) variant and Reynolds number considerations served as the primary focus of the workshop, and a simple wing-body variant of the CRM-HL was used as a verification test case. The HO-TFG was tasked with generating high-order curved meshes for these complex geometries, and computing high-order solutions using both Reynolds Averaged Navier-Stokes (RANS) and scale resolving Large Eddy Simulation(LES) formulations. While participation in the HO-TFG was limited, the effort produced curved meshes on highly-complex geometric configurations and computational results from two participants. The LES results demonstrate the potential for producing results comparable to 2nd-order accurate methods, but with fewer degrees of freedom. The RANS submission for this workshop does not demonstrate a benefit over 2nd-order schemes. However, the authors will argue a lack of understanding for optimal mesh distributions for high-order methods is the cause for the limited benefits observed for the RANS results. © 2025, American institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Reynolds number

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Approaching Metaheuristic Deep Learning Combos for Automated Data Mining

arXiv

引用

arXiv 2024年

作者： Assunção, Gustavo Menezes, Paulo Institute of Systems and Robotics University of Coimbra R. Silvio Lima Coimbra3030-194 Portugal Department of Electrical and Computer Engineering University of Coimbra R. Silvio Lima Coimbra3030-194 Portugal

Lack of data on which to perform experimentation is a recurring issue in many areas of research, particularly in machine learning. The inability of most automated data mining techniques to be generalized to all types of data is inherently related with their dependency on those types which deems them ineffective against anything slightly different. Meta-heuristics are algorithms which attempt to optimize some solution independently of the type of data used, whilst classifiers or neural networks focus on feature extrapolation and dimensionality reduction to fit some model onto data arranged in a particular way. These two algorithmic fields encompass a group of characteristics which when combined are seemingly capable of achieving data mining regardless of how it is arranged. To this end, this work proposes a means of combining meta-heuristic methods with conventional classifiers and neural networks in order to perform automated data mining. Experiments on the MNIST dataset for handwritten digit recognition were performed and it was empirically observed that using a ground truth labeled dataset’s validation accuracy is inadequate for correcting labels of other previously unseen data instances. © 2024, CC BY.

关键词： Adversarial machine learning

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