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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Huijie Dong Chunyang Zhao Tiezhu Qiao Jian Wang Di Chen Yan Meng Junzhi Yu Ministry of Education Key Laboratory of Advanced Transducers and Intelligent Control System Taiyuan University of Technology Taiyuan China Institute of Automation Laboratory of Cognitive and Decision Intelligence for Complex System Chinese Academy of Sciences Beijing China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China College of Electronics and Information Engineering Guangdong Ocean University Zhanjiang China

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named ‘CourierFish’. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks.

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Energy Efficiency Optimization for Full-Duplex D2D Communications Underlaying Distributed Antenna systems

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2024年

作者： Liu, Zhan Liao, Zhiyuan Li, Chunquan Zhang, Zhijun Yu, Junzhi Liu, P.X. Hunan University of Humanities Science and Technology School of Information Loudi417000 China Nanchang University School of Information Engineering Nanchang330031 China Jiangxi Provincial Key Laboratory of Intelligent Systems and Human-Machine Interaction Nanchang330031 China South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada

In this paper, we investigate the total system energy efficiency (EE) of full-duplex (FD) device-to-device (D2D) communications underlaying distributed antenna systems (DAS), where remote access units (RAUs), D2D users (DUs), and cellular users (CUs) are all capable of FD operation. Specifically, we jointly optimize subcarrier assignment and power allocation under the quality of service (QoS) requirements of CUs and DUs and the maximum power constraints of RAUs, CUs, and DUs. In addition, we propose a novel spectrum sharing strategy that allows each subcarrier to be assigned to multiple CUs and/or multiple D2D pairs (DPs) for flexibility. To solve the formulated non-convex optimization problem, we first employ fractional programming to transform the objective function in the optimization problem from the fractional form into the equivalent subtractive form. Then, an efficient iterative resource allocation algorithm is proposed, which needs to solve an inner problem in each iteration. After relaxing the variables and introducing penalty factors, the non-convex inner problem is transformed into a convex problem through the successive convex approximation (SCA) method and solved by iterative algorithm. Simulation results demonstrate that the proposed algorithm can considerably improve the system EE compared to other benchmark schemes. Furthermore, the proposed spectrum sharing strategy is superior to the existing sharing strategies. © 2017 IEEE.

关键词： Convex optimization

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Time-frequency decomposition-based weighted ensemble learning for motor imagery EEG classification

Time-frequency decomposition-based weighted ensemble learnin...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Zheng, Liangsheng Ma, Yue Li, Mengyao Xiao, Yang Feng, Wei Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (纸本)9781665436786

Motor imagery brain-computer interface system based on Electroencephalogram (EEG) is an effective way to help the disabled recover part of their motor abilities. However, decoding the movement intention contained in the EEG signal accurately presents many challenges. In this paper, we propose a time-frequency decomposition-based weighted ensemble learning (TFDWEL) method, which aims to improve the classification performance of motor imagery EEG signals. The TFDWEL method divides the EEG signal into multiple subsets, and uses four time-frequency processing methods to extract the time-frequency sub-bands of each subset. Then the feature extraction model and classifier model of each subset trained by the common spatial pattern (CSP) algorithm and the support vector machine (SVM) algorithm are used to build a set of base learners. The least square error estimation method is used to learn the weight of each base learner, and finally the weighted summation method is used to obtain the final decision. The classification performance of the TFDWEL method is evaluated on the BCI Competition IV Data Set 2b, and the results show that the classification accuracy of 81.58% can be obtained. Superior classification performance indicates that the TFDWEL method can be used in further research to help the rehabilitation of the disabled. © 2021 IEEE.

关键词： Electroencephalography

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A Secure Clustering Protocol with Fuzzy Trust Evaluation and Outlier Detection for Industrial Wireless Sensor Networks

arXiv

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arXiv 2022年

作者： Yang, Liu Lu, Yinzhi Yang, Simon X. Guo, Tan Liang, Zhifang The School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China The Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph GuelphONN1G2W1 Canada

Security is one of the major concerns in Industrial Wireless Sensor Networks (IWSNs). To assure the security in clustered IWSNs, this paper presents a secure clustering protocol with fuzzy trust evaluation and outlier detection (SCFTO). Firstly, to deal with the transmission uncertainty in an open wireless medium, an interval type-2 fuzzy logic controller is adopted to estimate the trusts. And then a density based outlier detection mechanism is introduced to acquire an adaptive trust threshold used to isolate the malicious nodes from being cluster heads. Finally, a fuzzy based cluster heads election method is proposed to achieve a balance between energy saving and security assurance, so that a normal sensor node with more residual energy or less confidence on other nodes has higher probability to be the cluster head. Extensive experiments verify that our secure clustering protocol can effectively defend the network against attacks from internal malicious or compromised nodes. © 2022, CC BY.

关键词： Uncertainty analysis

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A novel gait prediction method for soft exosuit base on limit cycle and neural network 22

A novel gait prediction method for soft exosuit base on limi...

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22nd IEEE International Conference on E-Health Networking, Application and Services, HEALTHCOM 2020

作者： Chen, Lingxing Chen, Chunjie Fang, Tao Zhang, Yu Liu, Youfu Wu, Xinyu Shenzhen Institutes of Adanced Technology Chinese Academy of Sciences Shenzhen China ShenZhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China

ISBN: (纸本)9781728162676

The important purpose of soft exosuit is to decrease the energy consumption of users by providing assistance. If there is something wrong with the judgment of the human gait during the assisting process, the assisting effect will be poor and even people's walking will be affected. A novel method is designed to predict human gait information in the paper, which utilizes the curve shape and mathematical characteristics of the Rayleigh oscillator equation in limit cycle to fit gait information. Only 1/4 gait cycle data is needed to input into the trained neural network to output an Rayleigh oscillator equation that can better predict the remaining gait cycle information. Data of four subjects on different terrains which include flat ground and upstairs are collected. Experiment results showed that the trained ANN model costs about 0.006s in CPU, it has a prediction speed similar to traditional prediction methods. Simultaneously the Rayleigh oscillator equation has good performance in predicting gait information, and it can show a higher stability and accuracy compared with traditional gait prediction methods. © 2021 IEEE.

关键词： Forecasting

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Vision-based soldering process parameters calculation for robotic soldering

Vision-based soldering process parameters calculation for ro...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Ren, Hao Wu, Xinyu Shang, Wanfeng Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China University of Chinese Academy of Sciences CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Chinese Academy of Sciences Shenzhen518055 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9781665436786

Robotic soldering has emerged as one of the key technologies for the through-hole technology (THT) assembly process. However, the determination of the soldering process parameters in those systems are still depends on engineer's experience. In this paper, we propose an automatic vision-based soldering process parameters determination method based on a mathematical model of standard solder joint. The system framework of this method and the detailed process of solder feeding volume calculation are also given. The proposed method is verified by experiments and compared with the soldering process parameters in published literature. Finally, we also analyze that the average computing time of the proposed method for new solder joints is 31.39ms, which is much faster than previous manual debugging method. © 2021 IEEE.

关键词： Soldering

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A novel soft exosuit based on biomechanical analysis for assisting lower extremity 22

A novel soft exosuit based on biomechanical analysis for ass...

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22nd IEEE International Conference on E-Health Networking, Application and Services, HEALTHCOM 2020

作者： Liu, Youfu Chen, Chunjie Lu, Jun Liu, Yida Zhang, Yu Wang, Zhuo College of Mechanical and Electrical Engineering Shaanxi University of Science and Technology Shenzhen China ShenZhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China

ISBN: (纸本)9781728162676

In the past two decades, with growing focus of lower limb exoskeleton, large variety of rigid exoskeletons were designed for medical rehabilitation and the other purposes. Compared with the rigid exoskeletons, which added extra inertial to low limb and restricted wearers' movement, the soft wearable lower extremity exoskeleton minimized the impact of these factors on the human body locomotion. In this paper, a novel design of exosuit that provided assistive force for both hip extension and flexion through the variation in hip joint dynamics during strides was proposed. Based on the change of hip moment, an assistance strategy and assistance force curve were came up with. PD type iterative learning control (ILC) method was introduced to reduce the error caused by wearing position and biological characteristics to improve assistance performance. To evaluate assistance performance, the metabolic cost of four subjects wearing exosuit and walking on treadmill at 5km/h in the situations of that without assistance, assisting both hip extension and hip flexion, and assisting hip extension respectively was measured. Compared with assisting hip extension only and wearing exosuit with no assistance, results indicated that the decrease in average net metabolic cost of assisting both hip extension and flexion was 0.445W/kg and 1.027W/kg respectively, corresponding to the average net metabolic cost rate decrease was 7.45% and 15.67%. © 2021 IEEE.

关键词： Exoskeleton (robotics)

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Generative Adversarial Learning for intelligent Trust Management in 6G Wireless Networks

arXiv

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arXiv 2022年

作者： Yang, Liu Li, Yun Yang, Simon X. Lu, Yinzhi Guo, Tan Yu, Keping The School of Communication and Information Engineering Chongqing University of Posts and Telecommunications China The School of Software Engineering Chongqing University of Posts and Telecommunications China The Advanced Robotics and Intelligent Systems Laboratory University of Guelph Canada The Hosei University Japan

Emerging six generation (6G) is the integration of heterogeneous wireless networks, which can seamlessly support anywhere and anytime networking. But high Quality-of-Trust should be offered by 6G to meet mobile user expectations. Artificial intelligence (AI) is considered as one of the most important components in 6G. Then AI-based trust management is a promising paradigm to provide trusted and reliable services. In this article, a generative adversarial learning-enabled trust management method is presented for 6G wireless networks. Some typical AI-based trust management schemes are first reviewed, and then a potential heterogeneous and intelligent 6G architecture is introduced. Next, the integration of AI and trust management is developed to optimize the intelligence and security. Finally, the presented AI-based trust management method is applied to secure clustering to achieve reliable and real-time communications. Simulation results have demonstrated its excellent performance in guaranteeing network security and service quality. © 2022, CC BY.

关键词： Wireless networks

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Structural Optimization of Photoacoustic Transducer with Pdms/Csnps Nanocomposite for Laser-Induced Nonlinear Surface Wave and its Application in Fatigue Crack Detection

SSRN

引用

SSRN 2023年

作者： Yao, Zhijun Li, Yehai Lv, Gaolong Chen, Dan Yang, Jian Guo, Shifeng Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China Institute of Intelligent Manufacturing Technology Shenzhen Polytechnic Shenzhen518055 China Department of Mechanical Materials and Manufacturing Engineering University of Nottingham Ningbo China Ningbo315100 China

Laser ultrasonics is a promising non-contact inspection technique but faces the challenges of low signal-to-noise ratio and low amplitude under the non-destructive thermoelastic regime. In this paper, an ultrasonic surface wave modulation method based on laser ultrasonics and photoacoustic transducer (PAT) is proposed and combined with nonlinear wave mixing technique to achieve non-contact detection of fatigue crack. The PAT comprised of candle soot nanoparticles and polydimethylsiloxane (PDMS) as well as a line-arrayed laser source modulated by a slit mask are firstly introduced to generate narrowband surface wave with high intensity and SNR under the thermoelastic regime. The thicknesses of the PDMS layers of PAT are thereafter optimized by analytical, numerical and experimental investigations to acquire narrowband surface wave with pure fundamental frequency component. Two modulated ultrasonic surface waves with frequencies of 2.1 MHz and 2.9 MHz are excited on a fatigued aluminum plate to generate nonlinear mixed components, and the ultrasonic responses over the fatigue crack regions are acquired by using a scanning laser Doppler vibrometer. The localization of fatigue crack with microscale is eventually acquired by mapping the nonlinear parameter of the mixed components, which proves it a reliable and nondestructive technique to inspect the fatigue crack. © 2023, The Authors. All rights reserved.

关键词： Transducers

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A one-step pseudolinear kalman filter for invasive target tracking in three-dimensional space

A one-step pseudolinear kalman filter for invasive target tr...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Zhang, Ying Liang, Rui Xu, Sheng Zhang, Liyuan Zhang, Ye Xiao, Dandan State Grid Tianjin Electric Power Company City West Power Supply Branch Tianjin300190 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China

ISBN: (纸本)9781665436786

This work studies the characteristics of the 3-dimensional (3D) pseudolinear Kalman filter (PLKF) proposed in the previous work [1] for angle-of-arrival (AOA) target tracking in the 3D space. The previous two-step 3D PLKF contains an xy-PLKF and a z-PLKF. This paper develops a one-step PLKF algorithm, which has low computational complexity. The estimation performance analysis of these two different PLKFs is provided. The one-step PLKF sacrifices the estimation accuracy to acquire a low computational complexity. In the distributed target tracking problem, the one-step PLKF can save a lot of communication costs compared with the two-step one. Furthermore, the stability of two PLKFs are also been simply proven. Simulation examples verify the effectiveness of the proposed one-step 3D PLKF to track an invasive target. Besides, the difference between the two PLKFs based on the theoretical analysis is also demonstrated by the simulation examples. © 2021 IEEE.

关键词： Target tracking

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