检索结果-内蒙古大学图书馆

IEEE Transactions on Intelligent Transportation systems 2024年第3期25卷 3202-3204页

作者： Xing Li Haotian Zhang Yajing Shen Lina Hao Wanfeng Shang School of Electrical Engineering and Intelligentization Dongguan University of Technology Dongguan China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China College of Computer Science and Technology Jilin University Changchun China Department of Biomedical Engineering City University of Hong Kong Hong Kong China School of Mechanical and Engineering Northeastern University Shenyang China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

In [1] , inaccuracies in several critical equations along with their accompanying descriptions appear in the article. Furthermore, some references are missing, and certain analyses of experiments are flawed.

关键词： Adaptive systems Data communication Optimization Intelligent transportation systems

A Bipolar Myoelectric Sensor-Enabled Human-Machine Interface Based On Spinal Module Activations

学校读者我要写书评

暂无评论

A Bipolar Myoelectric Sensor-Enabled Human-Machine Interface...

IEEE International Conference on robotics and Automation (ICRA)

作者： Chunzhi Yi Feng Jiang Guangming Lu Chifu Yang Zhen Ding Jianfei Zhu Jie Liu State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Heilongjiang China School of Computer Science and Technology Harbin Institute of Technology Harbin Heilongjiang China Pengcheng Laboratory Shenzhen Guangdong China Nanjing Jinling Hospital Clinical School Medical College Nanjing University Nanjing Jiangsu China AI Research Institute Harbin Institute of Technology Shenzhen Guangdong China

The surface electromyography (sEMG) signal-based human-machine interface (HMI) has been widely used for various scenarios of physical human-robot interaction. However, current HMIs based on bipolar myoelectric sensors are hindered by the limitations of global sEMG features, which are prone to variability and delay. In this letter, we define a HMI that takes advantage of the underlying neural information of spinal module activations from bipolar sEMG signals, inspired by recent findings of neural codes. Firstly, the spinal module activations are identified by the spiking trains of the muscle synergies extracted from bipolar sEMG signals. Secondly, we extract the information encoded in both firing rates and spike timings of the spinal module activation in a population coding manner, which follows the information encoding principle of neurons. Thirdly, we map the series of spinal module activations into gait phases, locomotion modes, joint moment and human identity in order to experimentally reveal the physiological information contained in the spinal module activations. The contained information and the benefit of our design are demonstrated and experimentally explained by the presented results and comparisons with the traditionally used global sEMG features. The proposed bipolar myoelectric sensor-enabled human-machine interface could contribute to various scenarios of physical human-robot interaction.

关键词： Sociology Neurons Human-robot interaction Sensor phenomena and characterization Muscles Robot sensing systems Encoding

An adaptable prosthetic socket: Regulating independent air bladders through closed-loop control

学校读者我要写书评

暂无评论

An adaptable prosthetic socket: Regulating independent air b...

IEEE International Symposium on Circuits and systems (ISCAS)

作者： Daniel Candrea Avinash Sharma Luke Osborn Yikun Gu Nitish Thakor Department of Biomedical Engineering Duke University Durham NC USA Department of Mechanical Engineering Indian Institute of Technology Delhi India Department of Biomedical Engineering Johns Hopkins University Baltimore MD USA State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Heilongjiang China Singapore Institute for Neurotechnology Singapore

ISBN: (纸本)9781509014279;9781467368537

During grasping or natural movement a prosthesis experiences varying loads, which can directly impact the comfort and fit of a socket on the user's residual limb. To alleviate this issue, four independent air bladders were integrated in a custom prosthetic socket, which contacted a model residual limb. The purpose of the bladders was to maintain specific pressures on the model residual limb to counteract pressure changes caused by an applied load. To sense pressure, calibrated custom piezoresistive sensors were placed between the air bladder and the model residual limb. A closed-loop algorithm was implemented to utilize sensor feedback and update airflow into each bladder to achieve a pressure equilibrium that maintains a static socket-limb system. The RMS error of internal pressure using pulse width modulation (PWM) bladder regulation decreased by 33% when compared no pressure regulation on the top bladder. We showed that this adaptive biomedical system for the human machine interface between a residual limb and socket can improve stability for prosthesis users using real-time pressure feedback.

关键词： Bladder Sockets Pulse width modulation Sensors Voltage control Prosthetics Valves

Conditional Generative Models for Simulation of EMG During Naturalistic Movements

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Ma, Shihan Clarke, Alexander Kenneth Maksymenko, Kostiantyn Deslauriers-Gauthier, Samuel Sheng, Xinjun Zhu, Xiangyang Farina, Dario The Department of Bioengineering Imperial College London United Kingdom The State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai China The Meta Robotics Institute Shanghai Jiao Tong University Shanghai China Neurodec Sophia Antipolis France Inria Centre Université Côte d’Azur Nice France

Numerical models of electromyographic (EMG) signals have provided a huge contribution to our fundamental understanding of human neurophysiology and remain a central pillar of motor neuroscience and the development of human-machine interfaces. However, whilst modern biophysical simulations based on finite element methods are highly accurate, they are extremely computationally expensive and thus are generally limited to modelling static systems such as isometrically contracting limbs. As a solution to this problem, we propose a transfer learning approach, in which a conditional generative model is trained to mimic the output of an advanced numerical model. To this end, we present BioMime, a conditional generative neural network trained adversarially to generate motor unit activation potential waveforms under a wide variety of volume conductor parameters. We demonstrate the ability of such a model to predictively interpolate between a much smaller number of numerical model’s outputs with a high accuracy. Consequently, the computational load is dramatically reduced, which allows the rapid simulation of EMG signals during truly dynamic and naturalistic movements. Copyright © 2022, The Authors. All rights reserved.

关键词： Numerical models

学校读者我要写书评

暂无评论

SSRN

SSRN 2024年

作者： Gao, Mingyu Song, Peng Liang, Zhipeng Huo, Liang Gao, Yulong Yang, Guohui Xie, Yunji Song, Yinghao Wang, Fei Liu, Junyan School of Mechatronics Engineering Harbin Institute of Technology Harbin150001 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China The 41st Institute of the Sixth Academy of CASIC Hohhot010010 China School of Electronics and Information Engineering Harbin Institute of Technology Harbin150001 China

This paper proposes a microwave defect characterization algorithm based on Convolutional Neural Networks (CNN). A defect dataset derived from reflection microwave signals, was manually compiled by detecting samples with critical defects. The CNN framework was utilized for precise classification of microwave signals, employing a classification encoding strategy to extract two-dimensional defect information and achieve automatic localization and imaging of defects. Multiple deep learning models were compared in both simulations and experiments, revealing that the proposed CNN exhibited significant advantages in feature extraction, enabling highly effective identification of internal defects even with a limited dataset. Compared with traditional algorithms, the detection accuracy of the proposed 1D-SENet has been improved by 53.35% and 50.66%, respectively, and can achieve detection of defects with a minimum size of Φ6mm. These validate the effectiveness of algorithm in intelligent and automated microwave characterization of delamination defects within composite materials. © 2024, The Authors. All rights reserved.

关键词： Composite materials

An Evolutionary Game based Secure Clustering Protocol with Fuzzy Trust Evaluation and Outlier Detection for Wireless Sensor Networks

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Yang, Liu Lu, Yinzhi Yang, Simon X. Zhong, Yuanchang 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 The State Key Laboratory of Power Transmission Equipment & System Security and New Technology School of Electrical Engineering Chongqing University Chongqing400044 China

Trustworthy and reliable data delivery is a challenging task in Wireless Sensor Networks (WSNs) due to unique characteristics and constraints. To acquire secured data delivery and address the conflict between security and energy, in this paper we present an evolutionary game based secure clustering protocol with fuzzy trust evaluation and outlier detection for WSNs. Firstly, a fuzzy trust evaluation method is presented to transform the transmission evidences into trust values while effectively alleviating the trust uncertainty. And then, a K-Means based outlier detection scheme is proposed to further analyze plenty of trust values obtained via fuzzy trust evaluation or trust recommendation. It can discover the commonalities and differences among sensor nodes while improving the accuracy of outlier detection. Finally, we present an evolutionary game based secure clustering protocol to achieve a trade-off between security assurance and energy saving for sensor nodes when electing for the cluster heads. A sensor node which failed to be the cluster head can securely choose its own head by isolating the suspicious nodes. Simulation results verify that our secure clustering protocol can effectively defend the network against the attacks from internal selfish or compromised nodes. Correspondingly, the timely data transfer rate can be improved significantly. © 2022, CC BY.

关键词： Sensor nodes

Simultaneously Calibration of Multi Hand-Eye Robot system Based on Graph

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Zhou, Zishun Ma, Liping Liu, Xilong Cao, Zhiqiang Yu, Junzhi The Institute of Automation Chinese Academy of Sciences Beijing100190 China The College of Electrical Engineering and Computer Science Australian National University Canberra2601 Australia The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The State Key Laboratory for Turbulence and Complex System Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Peking University Beijing100871 China

Precise calibration is the basis for the vision-guided robot system to achieve high-precision operations. systems with multiple eyes (cameras) and multiple hands (robots) are particularly sensitive to calibration errors, such as micro-assembly systems. Most existing methods focus on the calibration of a single unit of the whole system, such as poses between hand and eye, or between two hands. These methods can be used to determine the relative pose between each unit, but the serialized incremental calibration strategy cannot avoid the problem of error accumulation in a large-scale system. Instead of focusing on a single unit, this paper models the multi-eye and multi-hand system calibration problem as a graph and proposes a method based on the minimum spanning tree and graph optimization. This method can automatically plan the serialized optimal calibration strategy in accordance with the system settings to get coarse calibration results initially. Then, with these initial values, the closed-loop constraints are introduced to carry out global optimization. Simulation experiments demonstrate the performance of the proposed algorithm under different noises and various hand-eye configurations. In addition, experiments on real robot systems are presented to further verify the proposed method. © 2023, CC BY-SA.

关键词： Multipurpose robots

Long and Short-Term Constraints Driven Safe Reinforcement Learning for Autonomous Driving

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Hu, Xuemin Chen, Pan Wen, Yijun Tang, Bo Chen, Long School of Artificial Intelligence Hubei University Wuhan430062 China Key Laboratory of Intelligent Sensing System and Security Hubei University Ministry of Education Hubei Wuhan430062 China Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States State Key Laboratory of Multimodal Artificial Intelligence Systems State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing100190 China WAYTOUS Inc. Beijing100083 China Shenzhen518107 China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi’an710049 China

Reinforcement learning (RL) has been widely used in decision-making and control tasks, but the risk is very high for the agent in the training process due to the requirements of interaction with the environment, which seriously limits its industrial applications such as autonomous driving systems. Safe RL methods are developed to handle this issue by constraining the expected safety violation costs as a training objective, but the occurring probability of an unsafe state is still high, which is unacceptable in autonomous driving tasks. Moreover, these methods are difficult to achieve a balance between the cost and return expectations, which leads to learning performance degradation for the algorithms. In this paper, we propose a novel algorithm based on the long and short-term constraints (LSTC) for safe RL. The short-term constraint aims to enhance the shortterm state safety that the vehicle explores, while the long-term constraint enhances the overall safety of the vehicle throughout the decision-making process, both of which are jointly used to enhance the vehicle safety in the training process. In addition, we develop a safe RL method with dual-constraint optimization based on the Lagrange multiplier to optimize the training process for end-to-end autonomous driving. Comprehensive experiments were conducted on the MetaDrive simulator. Experimental results demonstrate that the proposed method achieves higher safety in continuous state and action tasks, and exhibits higher exploration performance in long-distance decision-making tasks compared with state-of-the-art methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Lagrange multipliers

A Novel Hybrid Method for Fault Diagnosis of Industrial Equipment Based on Vibration Signals

学校读者我要写书评

暂无评论

A Novel Hybrid Method for Fault Diagnosis of Industrial Equi...

Prognostics and system Health Management Conference (PHM-Qingdao)

作者： Sen Tao Kai Wang Peng Zeng Tianda Yu Hao Wu 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 University of Chinese Academy of Sciences Beijing China Shenyang China Nuclear Power Institute of China Chengdu China State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing China

Industrial equipment reliability is a critical issue that smart manufacturing systems must address. Implementation of online fault diagnosis for industrial equipment is a promising technology that can improve equipment reliability. Vibration analysis is a popular technique for equipment condition monitoring. For the non-linear and non-stationary features of industrial vibration signals, a hybrid model based on wavelet transform (WT), support vector machine (SVM), and grey wolf optimization algorithm (GWO) is proposed. The time-frequency domain features of fault signals are extracted by wavelet transform to solve the non-linearity of signals, and the obtained feature vectors are input into SVM for classification. Aiming at the problem of setting penalty coefficient and kernel function parameters, GWO is introduced to seek hyperparameters by using the hunting principle of wolves. In the experimental part, firstly, the comparison of the GWO-WT-SVM, GWO-SVM and SVM models was carried out. Secondly, Comparison with classical classification algorithms is made. Apparently, the GWO-WT-SVM model achieves higher accuracy than other models in bearing fault diagnosis.

关键词：

Design and 3D Printing of Lower Limb Prosthetic Socket *

学校读者我要写书评

暂无评论

Design and 3D Printing of Lower Limb Prosthetic Socket *

IEEE International Conference on Cyborg and Bionic systems (CBS)

作者： Sheng Li Bin Xie Ye Chen Xinyu Wu Guoxin Fang Yan Zhang Fei Gao Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China Shien-Ming Wu School of Intelligent Engineering South China University of Technology Guangzhou China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China State Key Laboratory of Powder Metallurgy Central South University Changsha Hunan China

ISBN: (数字)9798350388039

ISBN: (纸本)9798350388046

The prosthetic socket is a crucial interface connecting the residual limb to the prosthetic device, significantly affecting force transmission and wearer comfort. This work presents a comprehensive framework for design, simulation, and fabrication of the prosthetic socket. A 3D model of the residual limb, including the skeleton model and skin contour, is reconstructed from CT scan data. Using this model, the prosthetic socket and liner are designed based on biomechanical principles. The interaction force between the residual limb and the prosthetic socket and liner is simulated via finite element analysis (FEA) when the body weight of a below-knee amputee exerts on the prosthetic socket. Finally, the prosthetic socket and residual limb are fabricated using additive manufacturing (AM) technology, and a soft prosthetic liner is made of ethylene-vinyl-acetate (EVA) polymer. Clinical trials on a below-knee amputee were conducted to preliminarily test the prosthetic socket’s performance.

关键词： Limbs Solid modeling Sockets Biological system modeling Force Three-dimensional printing Skin Data models Finite element analysis Prosthetics