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Stiffness Estimation and Intention Detection for Human-Robot Collaboration

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

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

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

Probabilistic learning vector quantization on manifold of symmetric positive definite matrices

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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

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

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

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

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

Incremental Non-Gaussian Inference for SLAM Using Normalizing Flows

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arXiv 2021年

作者： Huang, Qiangqiang Pu, Can Khosoussi, Kasra Rosen, David M. Fourie, Dehann How, Jonathan P. Leonard, John J. MIT Computer Science and Artificial Intelligence Laboratory CambridgeMA02139 United States MIT Department of Nuclear Science and Engineering CambridgeMA02139 United States Robotics and Autonomous Systems Group DATA61 CSIRO BrisbaneQLD4069 Australia Northeastern University Department of Electrical and Computer Engineering BostonMA02115 United States NavAbility BostonMA02110 United States MIT Department of Aeronautical and Astronautical Engineering CambridgeMA02139 United States

This paper presents normalizing flows for incremental smoothing and mapping (NF-iSAM), a novel algorithm for inferring the full posterior distribution in SLAM problems with nonlinear measurement models and non-Gaussian factors. NF-iSAM exploits the expressive power of neural networks, and trains normalizing flows to model and sample the full posterior. By leveraging the Bayes tree, NF-iSAM enables efficient incremental updates similar to iSAM2, albeit in the more challenging non-Gaussian setting. We demonstrate the advantages of NF-iSAM over state-of-the-art point and distribution estimation algorithms using range-only SLAM problems with data association ambiguity. NF-iSAM presents superior accuracy in describing the posterior beliefs of continuous variables (e.g., position) and discrete variables (e.g., data association). Copyright © 2021, The Authors. All rights reserved.

关键词： Gaussian noise (electronic)

Dense r-robust formations on lattices

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Dense r-robust formations on lattices

IEEE International Conference on robotics and Automation (ICRA)

作者： Luis Guerrero-Bonilla David Saldaña Vijay Kumar Division of Decision and Control Systems in the School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Autonomous and Intelligent Robotics Laboratory (AIRLab) Lehigh University Bethlehem PA USA GRASP Laboratory University of Pennsylvania

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Robot networks are susceptible to fail under the presence of malicious or defective robots. Resilient networks in the literature require high connectivity and large communication ranges, leading to high energy consumption in the communication network. This paper presents robot formations with guaranteed resiliency that use smaller communication ranges than previous results in the literature. The formations can be built on triangular and square lattices in the plane, and cubic lattices in the three-dimensional space. We support our theoretical framework with simulations.

关键词： Lattices Robot kinematics Communication networks Robustness Robot sensing systems Energy consumption

Super-resolution multicolor fluorescence microscopy enabled by an apochromatic super-oscillatory lens with extended depth-of-focus

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arXiv 2022年

作者： Li, Wenli He, Pei Fan, Yulong Du, Yangtao Gao, Bo Chu, Zhiqin An, Chengxu Lei, Dangyuan Yuan, Weizheng Yu, Yiting Research & Development Institute of Northwestern Polytechnical University in Shenzhen College of Mechanical Engineering Ningbo Institute of Northwestern Polytechnical University Northwestern Polytechnical University Xi'An710072 China Northwestern Polytechnical University Xi'An710072 China Shaanxi Province Key Laboratory of Micro and Nano Electro-Mechanical Systems Northwestern Polytechnical University Xi'An710072 China Department of Materials Science and Engineering City University of Hong Kong 999077 Hong Kong The Institute of Ai and Robotics Fudan University Shanghai200433 China Key Laboratory of Spectral Imaging Technology of Chinese Academy of Sciences Xi'an Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xian710119 China Department of Electrical and Electronic Engineering Joint Appointment with School of Biomedical Sciences The University of Hong Kong 999077 Hong Kong

Multicolor super-resolution imaging remains an intractable challenge for both far-field and near-field based super-resolution techniques. Planar super-oscillatory lens (SOL), a far-field subwavelength-focusing diffractive lens device, holds great potential for achieving sub-diffraction-limit imaging at multiple wavelengths. However, conventional SOL devices suffer from a numerical aperture (NA) related intrinsic tradeoff among the depth of focus (DoF), chromatic dispersion and focus spot size, being an essential characteristics of common diffractive optical elements. Typically, the limited DoF and significant chromatism associated with high NA can lead to unfavorable degradation of image quality although increasing NA imporves the resolution. Here, we apply a multi-objective genetic algorithm (GA) optimization approach to design an apochromatic binary-phase SOL that generates axially jointed multifoci concurrently having prolonged DoF, customized working distance (WD) and suppressed side-lobes yet minimized main-lobe size, optimizing the aforementioned NA-dependent tradeoff. Experimental implementation of this GA-optimized SOL demonstrates simultaneous focusing of blue, green and red light beams into an optical needle of ∼0.5λ in diameter and >10λ in length (DoF) at 428 μm WD, resulting in an ultimate resolution better than λ/3 in the lateral dimension. By integrating this apochromatic SOL device with a commercial fluorescence microscope, we employ the optical needle to perform, for the first time, three-dimensional super-resolution multicolor fluorescence imaging of the "unseen" fine structure of neurons at one go. The present study provides not only a practical route to far-field multicolor super-resolution imaging but also a viable approach for constructing imaging systems avoiding complex sample positioning and unfavorable photobleaching. Copyright © 2022, The Authors. All rights reserved.

关键词： Needles

Variable Stiffness Control with Strict Frequency Domain Constraints for Physical Human-Robot Interaction

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arXiv 2020年

作者： Zou, Wulin Duan, Pu Chen, Yawen Yu, Ningbo Shi, Ling Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong Xeno Dynamics Co. Ltd Shenzhen China Institute of Robotics and Automatic Information Systems Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China

Variable impedance control is advantageous for physical human-robot interaction to improve safety, adaptability and many other aspects. This paper presents a gain-scheduled variable stiffness control approach under strict frequency-domain constraints. Firstly, to reduce conservativeness, we characterize and constrain the impedance rendering, actuator saturation, disturbance/noise rejection and passivity requirements into their specific frequency bands. This relaxation makes sense because of the restricted frequency properties of the interactive robots. Secondly, a gain-scheduled method is taken to regulate the controller gains with respect to the desired stiffness. Thirdly, the scheduling function is parameterized via a nonsmooth optimization method. Finally, the proposed approach is validated by simulations, experiments and comparisons with a gain-fixed passivity-based PID method. Copyright © 2020, The Authors. All rights reserved.

关键词： Frequency domain analysis