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检索条件"机构=Shenzhen Academy of Robotics of Robotics"

共 826 条记录，以下是31-40 订阅

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A Comprehensive Assessment of Lower Limb Muscle Fatigue Through Fusion of sEMG and VMG Signals 17

A Comprehensive Assessment of Lower Limb Muscle Fatigue Thro...

引用

17th International Convention on Rehabilitation Engineering and Assistive Technology, i-CREATe 2024

作者： Pan, Heng Song, Xiaoyu Rao, Haotian Wang, Can Wu, Xinyu Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent Sys-tem Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9798350355154

The measurement of lower limb muscle fatigue is crucial for Human-Machine Interaction (HMI) and the prevention of muscle injuries. This study aims to explore a method for assessing lower limb fatigue based on surface electromyography (sEMG) and vibromyography (VMG) signals, with the aim of improving the accuracy and sensitivity of muscle fatigue assessment. The muscle fatigue induction experiment was conducted by subjecting participants to sustained isometric contractions at 50 % of their maximal voluntary contraction (MV C) to induce a state of complete muscle fatigue, with five subjects participating. We employed the wavelet scattering technique to extract features from the sEMG and VMG signals, subsequently analyzing the combination of peak amplitude, root mean square (RMS), and median frequency (MDF) as indicators of muscle fatigue. By analyzing the differences and correlations between these fatigue indicators, it is possible to correlate muscle contraction intensity and muscle synergy, thereby making a detailed and reliable physiological assessment of muscle fatigue and comprehensively understanding the fa-tigue mechanism. This study provides a new assessment method for sports medicine and rehabilitation engineering, and provides theoretical support for fatigue monitoring and rehabilitation training. © 2024 IEEE.

关键词： fatigue-based feedback Muscle fatigue surface electromyo-graphy (sEMG) vibromyography (VMG) wavelet scattering

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Adaptive Adjustment of Factor's Weight for a Multi-Sensor SLAM 2

Adaptive Adjustment of Factor's Weight for a Multi-Sensor SL...

引用

2022 2nd International Conference on Computer, Internet of Things and Control Engineering, CITCE 2022

作者： Zhu, Zihan Zhang, Yi Wang, Weijun Feng, Wei Luo, Haowen Zhang, Yaojie Shenzhen Institute of Advanced Technology Chinese Academy of Sciences 518055 China University of Chinese Academy of Sciences Beijing100049 China Guangdong Provincial Key Lab of Construction Robotics and Intelligent Manufacturing Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong Provincial International Joint Research Center for Robotics and Intelligent Construction 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

A multi-sensor fusion simultaneous localization and mapping(SLAM) method based on factor graph optimization that can adaptively modify the weight of the graph factor is proposed in this study, to enhance the localization and mapping capability of autonomous robots in tough situations. Firstly, the algorithm fuses multi-lines lidar, monocular camera, and inertial measurement unit(IMU) in the odometry. Second, the factor graph is constructed using lidar and visual odometry as the unary edge and binary edge constraints, respectively, with the motion determined by IMU odometry serving as the primary odometry in the system. Finally, different increments of IMU odometry, lidar odometry and visual odometry are computed as favor factors to realize the adaptive adjustment of the factor's weight. The suggested method has greater location accuracy and a better mapping effect in complex situations when compared to previous algorithms. © Published under licence by IOP Publishing Ltd.

关键词： Optical radar

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A Spatial Feature Extraction Method for Enhancing Upper Limb Motion Intent Prediction in EMG-PR System 46

A Spatial Feature Extraction Method for Enhancing Upper Limb...

引用

46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Peng, Boxing Zhang, Haoshi Li, Xiangxin Zheng, Yue Li, Guanglin Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Shenzhen518055 China Southern University of Science and Technology Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Shenzhen518055 China Siat Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518055 China

ISBN: (纸本)9798350371499

High-Density Surface Electromyography (HD-sEMG) enriches motion intention pattern recognition systems by providing more spatial information. Multichannel linear descriptors (MLD) could provide a comprehensive description of the overall state characteristics within the muscle regions. In this study, an MLD-based spatial feature extraction method was proposed to capture differences and correlations in various muscle regions during movement, ultimately enhancing the system's classification accuracy. The performance of the feature extraction method was compared with traditional time domain feature extraction method under various classifiers and different movement types. The results show that employing the proposed method with the spatial features improves the classification error rates of combined movements from 11.14% to 7.28%, and better adaptability for all classifiers utilized in this study, which shows the effect of utilization of spatial information in different muscle regions. © 2024 IEEE.

关键词： Electromyography

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Learning Compliant Assembly Strategy From Demonstration

Learning Compliant Assembly Strategy From Demonstration

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Liu, Sheng Sheng, Juyi Ou, Yongsheng China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China

ISBN: (纸本)9798350327182

Compared with robots, humans can complete the different assembly tasks of parts flexibly and quickly. By teaching robots with human experiences, not only the industrial assembling tasks can be resolved, but also many other robot applications can be realized. The pose adjustment stage is the most critical part of the peg-in-hole assembly process. This paper analyzes the contact force in the pose adjustment stage and calculates the control variables that affect the assembly motion. Based on the Gaussian mixture model (GMM), the nonlinear mapping relationship between the control variables and the state variables during the assembly is established using the human demonstration data, and the parameters of the model are solved by the expectation maximization (EM) algorithm, and thus the human-like compliant assembly is completed by a robot. In order to verify the effectiveness of the demonstration-learning algorithm, a peg-in-hole assembly experiment was carried out using KUKA manipulator. Finally, the experiment shows that the proposed learning-based method not only improves the efficiency of the robot peg-in-hole assembly but also makes the manipulator have a satisfied adaptive ability to the complex environments in the assembly process. © 2023 IEEE.

关键词： Manipulators

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A Study of Prototypical Network Techniques for Cross-Subject EEG Analysis 27

A Study of Prototypical Network Techniques for Cross-Subject...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Liu, Wenchao Wang, Guagnyu He, Yuhong Bo, Hongjian Ma, Lin Li, Haifeng State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China Faculty of Computing Harbin Institute of Technology Harbin China Shenzhen Academy of Aerospace Technology Shenzhen China

ISBN: (纸本)9781643685489

Electroencephalography (EEG), a technique that uses electrodes on the scalp to record changes in cerebral electrical potentials, plays a key role in various brain-computer interface applications. However, due to the large differences in EEG distribution across subjects, how to accurately classify cross-subject EEG is still a challenge. In practice, it is unavoidable to collect data for each subject to perform calibration, which is cumbersome and expensive. In this paper, we propose a Cross Subject EEG Prototypical Network (CS-EEGPNet) for accurate few-shot EEG classification. To the best of our knowledge, we are the first to eliminate inter-subject distribution shift in few-shot EEG classification through multiple feature layers computation. Specifically, to avoid the effect of individual differences, we propose a few-shot feature normalization (FSFN) method, which uses the mean and variance of the same subject’s support set features to normalize the query set features. Meanwhile, we design a prototypical module based on auxiliary factors. This module utilizes learnable vectors to store category-related information for assisting the construction of prototypes, thus mitigating the effects of EEG’s randomness and non-stationary characteristics on cross-subject few shot classification. To validate the effectiveness of the method, we selecte the motor imagery paradigm, which is relatively complex in brain-computer interfaces, and test our method on the BCIC IV 2a and HGD datasets. The results demonstrate that our method significantly enhances EEG classification performance, achieving the state-of-the-art accuracies. © 2024 The Authors.

关键词： Electroencephalography

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GelPixel: A Single-Pixel-Based Tactile Sensor

GelPixel: A Single-Pixel-Based Tactile Sensor

引用

2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Huang, Binhua Li, Xiaoyu Sumari, Putra Ye, Chaoxiang Zhou, Zhenning Yin, Meng Yi, Zhengkun Wu, Xinyu Shenzhen Institute of Artificial Intelligence and Robotics for Society Siat Branch Shenzhen518055 China Universiti Sains Malaysia School of Computer Science 11800 Malaysia Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518055 China

ISBN: (纸本)9798350327182

In this paper, we present the design and development of a novel optical tactile sensor that uses a single-pixel color light-to-frequency converter (TCS3200) and spectral decoding to recognize presses at different positions. This innovative approach overcomes the limitations associated with camera-based sensors, such as increased manufacturing costs and shape restrictions, enabling potential integration as a skin-like layer over a robot's body. Our proposed direct light propagation structure demonstrates enhanced sensitivity and a broader measuring range compared to traditional reflection structures. Using Ecoflex as the elastomer, the sensor's design incorporates a three-layer structure, including an LED layer, an elastomer layer, and a color sensor layer. Experimental results demonstrate that the proposed sensor performs well in localization tasks, achieving over 95% accuracy using multi-target regression for rendering poked positions. This study demonstrates the potential of single-pixel-based tactile sensors in various applications and provides a foundation for further exploration in this area. © 2023 IEEE.

关键词： Tactile sensors

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A Sub-pixel Location Method of Circular PCB Markers Based on Partial Area Effect

A Sub-pixel Location Method of Circular PCB Markers Based on...

引用

2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Yang, Yingyuan Wang, Xianwen Luo, Sijin Liang, Guoyuan University of Chinese Academy of Sciences Beijing China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen China

ISBN: (纸本)9798350327182

With the rapid development of electronic manufacturing industry, automatic optical inspection (AOI) systems are widely applied to mark positioning and defect inspection of printed circuit board (PCB). As the most common mark, the accurate positioning of circle is of great importance in the wiring and assembly of the PCB. Various sub-pixel algorithms have been presented in the past decade. In this paper, we propose an improved version of sub-pixel edge location method based on partial area effect to acquire better sub-pixel points for fitting the circular marks. In stead of the simple one direction offset model, a composite offset model is adopted to diminish the positioning error as much as possible in the case of small gradient differences between horizontal and vertical directions. Besides, the constraints of both gradient magnitude and angle are also introduced for filtering the sub-pixel points at each edge pixel in order to effectively improve the quality of the fitted circle. Experiments conducted on synthetic and real PCB mark images have verified the better performance of the proposed method in terms of anti-interference and location accuracy. © 2023 IEEE.

关键词： Printed circuit boards

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Evaluation of Continual Learning Methods for Object Hardness Recognition

Evaluation of Continual Learning Methods for Object Hardness...

引用

2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Liu, Yiwen Fang, Senlin Liu, Chengliang Wang, Jingnan Mai, Ke Zhang, Yupo Yi, Zhengkun 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 Shenzhen Institute of Artificial Intelligence and Robotics for Society Siat Branch Shenzhen518055 China City University of Macau Faculty of Data Science 999078 China

ISBN: (纸本)9798350327182

How to solve the problem of continual learning of robotic tactile perception in an open, dynamic environment is a pressing task. Although continual learning has been extensively studied in computer vision, the evaluation of those algorithms does not provide insights on whether their solutions may help continual learning in the context of tactile robotics. In this paper, we propose a continual learning scenario in the robotic tactile domain, and design experiments with tactile hardness dataset that allow us to compare the performance of many continual learning algorithms in the tactile domain. We examine the performance of regularization-based and replay methods in the tactile domain and discuss the effect of replay number on model performance. We show that regularization-based methods do not perform well on the tactile dataset. On the contrary, replay methods can maintain better anti-forgetting performance, but the number of model parameters will be larger, and the training time will be longer. We also found that the replay ratio should be higher than 0.2 to maintain the performance of the replay method on the tactile hardness dataset. © 2023 IEEE.

关键词： robotics

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Optimal Piping Robot Design for Inner Pipe Operations

Optimal Piping Robot Design for Inner Pipe Operations

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Heping Chen Siwen Fang Shenzhen Academy of Robotics Shenzhen China

Piping robots that work inside pipes are widely used in nuclear, oil and gas industries. These robots can perform inner pipe operations such as in-spection, cleaning and grinding inside pipes. No matter what the operation is, the ability to move smoothly inside a pipe is very important. Pipes always have joints, turns and elbows that constrain the dimensionality of piping robots. In this paper, we present an optimization method to optimize the dimensionality of piping robots. Once the pipe's parameters are known, an optimization method is formulated to maximize the volume of a piping robot to ensure enough space for powerful actuators to perform different tasks. The proposed method is validated by fabricating a piping robot based on the optimized parameters for a given pipe. Experiments were performed and the results show that the robot can move smoothly inside the pipe.

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Flexible Sensors Used for Lower Assisting Exoskeleton 16th

Flexible Sensors Used for Lower Assisting Exoskeleton

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Xiao, Yang Chen, Chunjie Liu, Yao Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9789819964857

In recent years, with the aging of the social population, exoskeleton robots have a wide range of application prospects in rehabilitation assistance, walking assistance, and physical expansion. However, the sensors developed for traditional robots currently have problems such as poor wearability, poor biocompatibility, and poor adaptability. To realize human-machine motion coordination assistance with multiple degrees of freedom and multiple motion states more effectively, and improve the flexibility, real-time performance, and reliability of the interaction between the wearer and the exoskeleton, it is necessary to design a set of flexible sensing systems to monitor the wearer’s motion status. It provides intelligent sensing technology support for adaptive control of exoskeleton in complex environments. This paper proposes a new flexible stretchable capacitive sensor and introduces its selection and manufacturing process. In the following experiments, three different slopes in the static experiment and dynamic experiment were used to test its performance and explore the accuracy and stability of its angle measurement. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Capacitive sensors

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