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Determination of the Correlation between Process Parameters and Kerf Characteristics in Abrasive Waterjet Milling of High Strength 7075-T6 Aluminum Alloy

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Procedia Manufacturing 2020年 51卷 812-817页

作者： Panagiotis Karmiris-Obratański Rafał Kudelski Nikolaos E. Karkalos Angelos P. Markopoulos AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics Department of Manufacturing Systems al. Mickiewicza 30 30-059 Cracow Poland National Technical University of Athens School of Mechanical Engineering Laboratory of Manufacturing Technology Heroon Polytechniou 9 15780 Athens Greece

Non-conventional manufacturing processes are often advantageous compared to conventional ones, as they can achieve high productivity in demanding cases. Abrasive waterjet (AWJ) machining is one of the most established non-conventional machining processes, which can achieve high material removal rates without leading to undesired workpiece material alterations and can render a large variety of shapes. In the present work, experiments regarding the AWJ milling of high strength 7075-T6 aluminum alloy are conducted with a view to correlate the process parameters, such as waterjet pressure, jet standoff distance, jet traverse speed and abrasive mass flow rate with depth of penetration, width and taper angle of the produced kerf. After the correlation between input and output parameters of the process is established, statistical analysis enables the determination of the influence of input parameters on output quantities and finally, appropriate process conditions for the regulation of depth of cut and kerf characteristics are derived.

关键词： Abrasive waterjet milling aluminum 7075-T6 depth of penetration kerf width kerf taper angle

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Surface Topography of Ti 6Al 4V ELI after High Power EDM

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Procedia Manufacturing 2020年 47卷 788-794页

作者： Panagiotis Karmiris-Obratański Krzysztof Zagórski Jacek Cieślik Emmanouil Lazaros Papazoglou Angelos Markopoulos AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics Department of Manufacturing Systems al. Mickiewicza 30 30-059 Cracow Poland National Technical University of Athens School of Mechanical Engineering Laboratory of Manufacturing Technology Heroon Polytechniou 9 15780 Athens Greece

Titanium alloys find extensive applications in the modern aerospace and offshore industry, as well in the field of biomedical implants. Nevertheless, the titanium inherent thermo-physical properties (low thermal conductivity and high chemical reactivity) make it a hard to machine material. For the efficient machining of titanium alloys, non-conventional machining processes are employed. Electrical Discharge Machining (EDM) is a non-contact machining process, in which the material removal occurs through repetitive electrical sparks. The capabilities of machining any electrically conductive material, regardless of its thermo-physical and other properties, render it as one of the most widely used non-conventional machining processes. As titanium alloys are used in high-quality parts and products, the integrity and texture of the machined surface constitute an essential parameter. The current study presents an experimental investigation of the surface texture and integrity of Ti6Al4V ELI after its machining with high power EDM. Namely, a full-scale experiment has been carried out, for pulse currents up to 65A and pulse-on time up to 200 μs, using graphite electrode. The surface texture (ST) and integrity has been estimated in terms of arithmetic mean height (Sa), the maximum height of scale-limited surface (Sz), maximum peak height (Sp), maximum pit height (Sv) and skewness of the scale-limited surface (Ssk). Additionally, through microscopy observation, the surface topography and integrity have been estimated, distinguishing and characterizing the surface cracks and micro-cracks. For all the above mentioned ST parameters, an Analysis of Variance (ANOVA) test has been performed.

关键词： Electrical Discharge Machining Titanium alloy Surface topography high power

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Micro Robotic Manipulation System for the Force Stimulation of Muscle Fiber-like Cell Structure

Micro Robotic Manipulation System for the Force Stimulation ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Xie Chen Qing Shi Shingo Shimoda Tao Sun Huaping Wang Qiang Huang Toshio Fukuda Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China Intelligent Behavior Control Collaboration Unit RIKEN Center of Brain Science Nagoya Japan Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

Many previous works have facilitated muscle cell (C2C12) alignment to form fiber-like cell structures. However, there still remains a challenge how to induce C2C12 myoblasts in the cell structures to differentiate into matured myocytes to form a functional muscle tissue, while external mechanical stimulation has been proved to have good effects on proliferation and differentiation of myoblasts. In this paper, we proposed a vision-based micro robotic manipulation system to achieve automatic mechanical stimulation for one single muscle fiber-like cell structures (MFCS). A tube, which is attached to a three degree-of-freedom (DOF) manipulator, and a probe are employed to apply the uniaxial mechanical stimulation to train the MFCS. To measure the force applied on MFCS, a vision-based measuring and correction method is utilized, which decrease the error by 74%. Moreover, based on the viscoelastic property of the MFCS, a feedback control algorithm has been applied to compensate for the force loss to realize the force stimulation. And the final value of force remains 699 ± 1μN after 110s experiment.

关键词： Force measurement Force Measurement uncertainty Muscles Manipulators Feedback control Electron tubes

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Online Parameter Estimation For Uncertain Robot Manipulators With Fixed-time Convergence

Online Parameter Estimation For Uncertain Robot Manipulators...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Chengzhi Zhu Yiming Jiang Chenguang Yang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China National Engineering Laboratory for Robot Visual Perception and Control Hunan University Changsha China Bristol Robotics Laboratory University of the West of England Bristol UK

ISBN: (数字)9781728151694

ISBN: (纸本)9781728151700

For traditional parameter estimation schemes of uncertain robot, most of them were proposed to identify unknown parameter with desired precision, but few of them focused on the convergence time. Recently finite-time estimation techniques have been proposed by scholars to achieve estimation in finite time. In this paper, we proposed a novel estimation scheme for uncertain robot systems with fixed time instead of finite time. In order to avoid using acceleration signals during the estimation, a kind of auxiliary filtering technique was employed. Besides, a continuous and recursive update law was employed for the parameter estimation such that the computational burdens of real-time inversion of square matrices could be avoided. Finally the effectiveness of the identification algorithm is verified based on a 2-DOF uncertain robot model.

关键词： Parameter estimation Filtering Heuristic algorithms Estimation Real-time systems Manipulator dynamics Convergence

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Vector Sensor Beam Steering for Underwater Acoustic Communications

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Proceedings of Meetings on Acoustics 2020年第1期42卷

作者： Fabricio de Abreu Bozzi Sergio M. Jesus 1Laboratory of Robotics and Engineering Systems (LARSys) University of Algarve Faro 8000-218 PORTUGAL fabriciobozzi@*** 2Laboratory of Robotics and Engineering Systems (LARSys) University of Algarve Faro 8005-139 PORTUGAL sjesus@ualg.pt

Acoustic Vector Sensors (VS) have been widely used for direction-of-arrival estimation in the past, while the employment of VS for underwater communications is a recent topic. Due to its compact size, VS may be used as a receiver in applications such as on board of Unmanned Underwater Vehicles (UUV), providing higher maneuverability and operational capabilities. Thus, in this study, the communication performance of a VS beam-steering technique is quantified. The performance analysis is made comparing the VS beam-steering with the VS time-reversal method in a shallow water simulation. The underwater channel is given by the seismo-acoustic propagation model, OASES. A Phase Shift Keying (PSK) modulation is adopted and the receiver includes a Decision Feedback Equalizer. An individual analysis of horizontal and vertical particle velocity is made to show the steering effects in the error performance. Moreover, as the steering angle is range-dependent, a comparison between methods is performed varying the range. The result indicates that the optimum steering angle, which brings less error, may not be related to the source direction. Furthermore, the proposed receiver shows the outperformance comparing to the time-reversal in both SNR and range, demonstrating the spatial filter advantage provided by this co-located sensor.

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Stiffness Estimation and Intention Detection for Human-Robot Collaboration

Stiffness Estimation and Intention Detection for Human-Robot...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Xiongjun Chen Yiming Jiang Chenguang Yang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China National Engineering Laboratory for Robot Visual Perception and Control Hunan University Changsha China Bristol Robotics Laboratory University of the West of England Bristol UK

ISBN: (数字)9781728151694

ISBN: (纸本)9781728151700

In this paper, we propose a stiffness estimation and intention detection method for human-robot collaboration. The human arm endpoint stiffness can be obtained according to the muscle activation levels of the upper arm and the human arm configurations. The estimated endpoint stiffness of human arm is matching to the robot arm joint stiffness through an appropriate mapping. The motion intention of human arm is detected based on the wrist configuration which is recognized by a Myo armband attached at the forearm of the operator. In order to reduce the time of feature engineering to ensure the performance of real-time collaboration, the wrist configuration recognition is realised based on the neural learning algorithm. The sEMG of the human forearm is directly fed into the neural network after processing by filters and sliding windows. The force sensor at the end of the robot arm is embedded in the feedback loop to make the robot arm better adapted to the operator's movement. The results of experiments performed on Baxter robot platform illustrate a good performance and verifies the proposed method.

关键词： Wrist Neural networks Collaboration Estimation Robot sensing systems Manipulators Robots

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Diffusive nonreciprocity and thermal diode

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Physical Review B 2021年第1期103卷 014307-014307页

作者： Ying Li Jiaxin Li Minghong Qi Cheng-Wei Qiu Hongsheng Chen Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation College of Information Science and Electronic Engineering Zhejiang University Hangzhou 310027 China ZJU-Hangzhou Global Science and Technology Innovation Center Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Zhejiang University Hangzhou 310027 China International Joint Innovation Center ZJU-UIUC Institute The Electromagnetics Academy at Zhejiang University Zhejiang University Haining 314400 China Department of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 China

Wave propagation and diffusion in linear materials preserve local reciprocity in terms of a symmetric Green's function. For wave propagations, the relation between the fields entering and leaving a system is more relevant than the detailed information about the fields inside it. In such cases, the global reciprocity of the scattering off a system through several ports is more important, which is defined as the symmetric transmission between the scattering channels. When a two-port system supports nonreciprocal (electromagnetic, acoustic) wave propagation, it is a (optical, phonon) diode directly following the definition. However, to date no concrete definition or discussion has been made on the global reciprocity of diffusive processes through a multiple-port system. It thus remains unclear what are the differences and relations between the three concepts, namely, local nonreciprocity, global nonreciprocity, and diode effect in diffusion. Here, we provide theoretical analysis on the frequency-domain Green's function and define the global reciprocity of heat diffusion through a two-port system, which has a different setup from that of a thermal diode. We further prove the equivalence between a heat transfer system with broken steady-state global reciprocity and a thermal diode, assuming no temperature-dependent heat generation. The validities of some typical mechanisms in breaking the diffusive reciprocity and making a thermal diode have been discussed. Our results set a general background for future studies on symmetric and asymmetric diffusive processes.

关键词： Diffusion Heat transfer Metamaterials Diodes Green's function methods

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Probabilistic learning vector quantization on manifold of symmetric positive definite matrices

arXiv

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arXiv 2021年

作者： Sonna, Fengzhen Tang Feng, Haifeng Tino, Peter Si, Bailu Ji, Daxiong State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China School of computer Science University of Birmingham BirminghamB15 2TT United Kingdom School of Systems Science Beijing Normal University Beijing100875 China Institute of Marine Electronics and Intelligent Systems Ocean College Zhejiang University Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province Engineering Research Center of Oceanic Sensing Technology and Equipment Ministry of Education Zhoushan316021 China

In this paper, we develop a new classification method for manifold-valued data in the framework of probabilistic learning vector quantization. In many classification scenarios, the data can be naturally represented by symmetric positive definite matrices, which are inherently points that live on a curved Riemannian manifold. Due to the non-Euclidean geometry of Riemannian manifolds, traditional Euclidean machine learning algorithms yield poor results on such data. In this paper, we generalize the probabilistic learning vector quantization algorithm for data points living on the manifold of symmetric positive definite matrices equipped with Riemannian natural metric (affine-invariant metric). By exploiting the induced Riemannian distance, we derive the probabilistic learning Riemannian space quantization algorithm, obtaining the learning rule through Riemannian gradient descent. Empirical investigations on synthetic data, image data, and motor imagery EEG data demonstrate the superior performance of the proposed method. © 2021, CC BY-NC-SA.

关键词： Learning algorithms

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Application of Iterative Learning Control in X-Y Precision Planar Motion Platform

Application of Iterative Learning Control in X-Y Precision P...

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Chinese Automation Congress (CAC)

作者： Hongyu Yan Danping Jia Tao Zhang Hualiang Zhang Yingjie Xiong Xu Lu Yang Liu School of Artificial Intelligence Shenyang University of Technology Shenyang China School of Information Science and Engineering Shenyang University of Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Electrical Engineering Dalian University of Technology Dalian China College Of Information Science and Engineering Northeastern University Shenyang China

ISBN: (纸本)9781665426480

The size of the tracking error is one of the important indicators to measure the control system of the X-Y Precision Planar Motion Platform. Iterative learning control (ILC) can obtain higher tracking accuracy through multiple iterations. However, it is found in experiments that the tracking error of the XY precision motion stage using ordinary PD-type iterative learning will eventually fluctuate in a relatively range, and some high-frequency Noise will seriously affect the stability of the system after many iterations. Aiming at the above problems, a PD-type variable gain open-closed loop ILC with a low-pass filter is proposed. This control scheme can effectively remove high-frequency noise and reduce tracking errors. Finally, a hardware-in-the-loop real-time simulator is used to conduct a comparative experiment. Through comparison with PID controller and ordinary PD-type ILC, the experimental consequence show that this arithmetic has a smaller tracking error than the other two algorithms.

关键词： Tracking loops Tracking Low-pass filters Control systems Size measurement Stability analysis Real-time systems

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Haptic display for virtual reality: progress and challenges

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Virtual Reality & Intelligent Hardware 2019年第2期1卷 136-162页

作者： Dangxiao WANG Yuan GUO Shiyi LIU Yuru ZHANG Weiliang XU Jing XIAO State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100083China Beijing Advanced Innovation Center for Biomedical Engineering Beihang UniversityBeijing 100083China Peng Cheng Laboratory Shenzhen 518055China Department of Mechanical Engineering University of AucklandAuckland 1142New Zealand School of Computer Science and the Robotics Engineering Program Worcester Polytechnic InstituteWorcesterMA 01609-2280USA

Immersion, interaction, and imagination are three features of virtual reality (VR). Existing VR systems possess fairly realistic visual and auditory feedbacks, and however, are poor with haptic feedback, by means of which human can perceive the physical world via abundant haptic properties. Haptic display is an interface aiming to enable bilateral signal communications between human and computer, and thus to greatly enhance the immersion and interaction of VR systems. This paper surveys the paradigm shift of haptic display occurred in the past 30 years, which is classified into three stages, including desktop haptics, surface haptics, and wearable haptics. The driving forces, key technologies and typical applications in each stage are critically reviewed. Toward the future high-fidelity VR interaction, research challenges are highlighted concerning handheld haptic device, multimodal haptic device, and high fidelity haptic rendering. In the end, the importance of understanding human haptic perception for designing effective haptic devices is addressed.

关键词： Haptic display Virtual reality Desktop haptics Surface haptics Wearable haptics Multimodal haptics

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