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检索条件"机构=Advanced Robotics Technology and Systems Lab"

共 197 条记录，以下是31-40 订阅

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Development of a Lower Limb Gait Asymmetry Index with Cyclogram Analysis Using Image Processing

Development of a Lower Limb Gait Asymmetry Index with Cyclog...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Sepideh Etaati Fatemeh Javaherat Mehdi Delrobaei Department of Mechatronics Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Advanced Robotics and Automated Systems lab. Faculty of Mechanical Engineering K. N. Toosi University of Technology Tehran Iran

ISBN: (数字)9798331529734

ISBN: (纸本)9798331529741

Ahstract- This study focuses on developing a gait asymmetry index and applying image processing techniques to cyclogram analysis. We evaluated gait asymmetry under different walking conditions, specifically examining the effects of wearing a knee brace and holding a weight in hand. Using inertial measurement units (IMUs), we collected gait data to analyze knee, hip, and ankle angles in the sagittal plane. The joint kinematics data were assessed using our proposed asymmetry index, which combines image processing techniques and linear regression models. The proposed asymmetry index incorporates cyclogram area, trend symmetry, and the longest length of the cyclogram shape, effectively capturing variations in symmetry and providing a comprehensive measure. The results demonstrate that the proposed asymmetry index can effectively distinguish between different gait conditions. The findings potentially offer insights for researchers and clinicians in human biomechanics, aiding in the planning of interventions and the assessment of motion patterns, as well as for developers of bipedal walking robots in the field of robotic locomotion, enhancing their ability to design hardware and evaluate motion patterns.

关键词： Legged locomotion Knee Biomechanics Limbs Shape Image processing Market research Indexes Robots Hip

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Multiple Sensor Fusion-Based Positioning Robot for Steam Generator Inspection

Multiple Sensor Fusion-Based Positioning Robot for Steam Gen...

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Sensor technology and Control (ISSTC), International Symposium on

作者： Jingwei You Shouqi Wei Xiong Wu Jianquan Sun Department of Electrical Engineering Guilin University of Electronic Technology Guilin China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems Shenzhen China

Nuclear energy is presently the clean energy source most likely to massively displace fossil energy, and the secondary side of the steam generator is an important part of a nuclear power plant. Due to the small space of the secondary side of the steam generator and the confinement of the vessel, the precise positioning of the robot inside the steam generator cannot be achieved by a single sensor alone. This paper introduces a multi-sensor fusion steam generator secondary side inspection robot. Primary emphasis is on data fusion of multiple sensors, such as laser sensors, cameras, IMU, and wheel encoder. First of all, this paper integrates data from wheel encoder data and IMU data by using extended Kalman filtering (EKF), which decreases the drift error during the motion and enhances the robot positioning precision. Afterwards, we incorporate laser ranging sensors and camera picture data to enhance the overall spatial sensitivity of the robot through particle filtering algorithms. Experiments show that the robot works reliably and has high positioning accuracy.

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Design and simulation of a hip exoskeleton for lateral walking

Design and simulation of a hip exoskeleton for lateral walki...

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

作者： Zhang, Zhewen Cao, Wujing Chen, Chunjie Yu, Hongliu Wu, Xinyu Meng, Qiaoling Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System University of Shanghai for Science and Technology Rehabilitation Engineering and Technology Institute CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology

ISBN: (纸本)9781665436786

In this article, a rehabilitation exoskeleton assisted by lateral walking is designed to help patients with lower limb movement disorders to solve the problem of lateral walking assistance, so as to achieve the effect of rehabilitation training. Based on the characteristics of lateral movement of human body, the exoskeleton designed in this paper uses linear push rod motor and thigh binding to assist hip abduction and adduction respectively. Based on the research of human transverse movement gait, a reasonable linkage mechanism was designed and kinematics simulation was carried out. The dynamics model of human lower limbs was established and calculated with MATlab simulation software. the moment of hip joint lateral movement is obtained. Finally, the structural parameters of the driving mechanism were analyzed by dynamic simulation, and the simulation results were compared with the target motion function to verify the rationality of the design. © 2021 IEEE.

关键词： MATlab

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A Novel Multi-Stream Informer Used for Lower Extremity Joint Angle Estimation 12

A Novel Multi-Stream Informer Used for Lower Extremity Joint...

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12th International Conference on CYBER technology in Automation, Control, and Intelligent systems, CYBER 2022

作者： Zhou, Xin Zhang, Liming Liu, Jiaqing Ye, Jiancong Wang, Can Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China University of Science and Technology of China China University of Chinese Academy of Sciences China South China University of Technology China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

In lower extremity exoskeleton rehabilitation systems, synergy and proportionality between the human lower extremity and the exoskeleton robot have been a critical goal to pursue. In recent years, changeable deep learning models based on multi-source signals have been used for lower limb continuous motion estimation. During the process, multimode signals are fed into the time processing model as time series. However, there are some deficiencies in this framework, on the one hand, what kind of multi-source combination can be more efficient;on the other hand, most of the existing models need several iterations or network stacking to complete the extraction of temporal information. This study set out to address the above problems, we put forward Multi-Stream Informer (MS-Informer), using Multi-Stream combination and sparse attention mechanisms for lower limb continuous motion estimation. In the experiment, we compare MS-Informer and Temporal Convolutional Network (TCN) and Long Short-term Memory (LSTM) under distinctive multi-source combinations. In summary, MS-informer performs well in multiple evaluations compared with other models. Experimental results illustrate that the MS-Informer is more efficacious in lower limb joint angle estimation and is a promising method for achieving coordinated control of lower limb exoskeletons. © 2022 IEEE.

关键词： Motion estimation

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Test-Stand Development and Performance Analysis of RoboWalk Assistive Device

Test-Stand Development and Performance Analysis of RoboWalk ...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： S. Ali A. Moosavian Omid Mahdizadeh Vahid Akbari Mahdi Nabipour Sina Ghanaat Shahin Naeemi Sina Hallajian Arash T. Beydokhti Department of Mechanical Engineering Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems (ARAS) Lab K. N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781665454537

Robotic devices are increasingly studied for the rehabilitation purposes of the lower limb disabilities. Wearable assistive devices such as exoskeletons have been recognized as a practical solution to increase the power and maneuverability of human beings in industries, as well as rehabilitation, elderly care, and sports exercises. RoboWalk is a lower limb assistive device that has been designed in ARAS lab at KNTU. To guarantee its proper performance, a Test-Stand is designed and manufactured with extended toolkit options. To validate the simulation results of various scenarios, is the main goal of developing this Test-Stand. Also, to examine the electronics boards and subsystems, the correct interaction between the sensors and the actuators, and investigate the performance of the main control loop, and so on, the Test-Stand is highly useful. In this paper, these various aspects of design and manufacturing of RoboWalk test stand are presented. Stress analyses in SOLIDWORKS software showed that the design of the proposed device is capable to handle the required tasks. Finally, a positioning task is implemented, which reveals the merits of the designed Test_Stand.

关键词： Performance evaluation Simulation Exoskeletons Software Sensors Manufacturing Assistive devices

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Accurate Prediction of Knee Joint Angles Using a Hybrid CNN-LSTM-Attention Network from Surface Electromyography

Accurate Prediction of Knee Joint Angles Using a Hybrid CNN-...

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IEEE International Conference on robotics and Biomimetics

作者： Zhuo Wang Hui Chen Fangliang Yang Xiangyang Wang Xinyu Wu Chunjie Chen Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong Provincial Key Lab 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 Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

In various fields such as robotics, rehabilitation, biomechanics, human-machine interfaces, and clinical research, human motion prediction has extensive applications. A hybrid networks model based on Convolutional Neural Network-Long Short-Term Memory-Attention (CNN-LSTM-Attention) was employed in this paper to extract features from the high-dimensional space and time series of surface electromyography (sEMG) data for continuous prediction of knee angles. Five able-bodied subjects participated in the study, walking at a self-selected pace while six surface electromyography (sEMG) signals from muscles involved in knee flexion and extension, along with knee angles, were synchronously recorded. The performance was assessed using the root mean square error (RMSE), Pearson Correlation Coefficient $(r)$ , and coefficient of determination $(R^{2})$ between estimated and measured knee joint angles. Compared to the CNN, LSTM, and CNN-LSTM algorithms, the adopted method estimated knee angles more accurately, achieving an average RMSE, $\rho$ , and $R^{2}$ of $3.09\pm 0.90,\ 0.9911 \pm 0.0052$ , and $0.9817\pm 0.0108$ , respectively. As the advance time increased, the accuracy of knee joint angle estimation decreased, particularly when the advance time reached 100 ms, at which point the RMSE is 4.83 degress. In addition, the computing time of the prediction model was less than 1 ms, which was shorter than the advance time 100 ms it could predict, thereby facilitating real-time computation in practical environments. Compared to previous studies, the proposed method excelled at extracting features directly from raw signals, avoiding the need for handcrafted feature extraction. Consequently, the model effectively achieved continuous and accurate predictions of joint motion angles and demonstrated potential to reduce latency in the human-machine interface.

关键词： Knee Accuracy Computational modeling Predictive models Feature extraction Electromyography Convolutional neural networks Wearable devices Long short term memory Robots

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Forward Kinematics Development of a 3-RRS Parallel Manipulator for Real-Time Control

Forward Kinematics Development of a 3-RRS Parallel Manipulat...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： S. Ali A. Moosavian Omid Mahdizadeh Sina Hallajian Sara Ashrafi Mohammad Jamali Vahid Akbari Department of Mechanical Engineering Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems (ARAS) Lab. K. N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781665454537

In control of parallel robots, forward kinematics calculation is mainly required. In some studies, obtained equations are solved numerically with massive calculations that is not acceptable for control implementations. This paper introduces a new method to extract forward kinematics for a 3- RRS robot. This method calculates the kinematics of passive joints with two separated equations, which can be solved to decrease the total computation demands. Also, a new weight compensation mechanism is proposed to improve the dynamic response by a linear pneumatic actuator placed between the ground and the end-effector. On the other hand, to use various control algorithms, the position of the rolling ball on the end- effector (moving platform) must be measured. This is performed using Convolutional Neural Networks (CNNs) as image processing algorithms. Since the system must work quickly for a high-frequency task, the proposed image processing algorithm can provide the desired fast feedback. Experimental results reveal the merits of the above-described proposed modules.

关键词： Pneumatic actuators Image processing Heuristic algorithms Kinematics Position measurement Pneumatic systems Mathematical models

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Rehabilitation Training of Spinal Cord Injured Individuals by a Self-Balancing Exoskeleton Robot

Rehabilitation Training of Spinal Cord Injured Individuals b...

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

作者： Wentao Li Jinke Li Yong He Dingkui Tian Feng Li Jianquan Sun Xinyu Wu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China SIAT CUHK Joint Laboratory of Robotics and Intelligent Systems Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China China Construction Third Bureau First Engineering MEP Co. Ltd. Shenzhen China

Physical therapy plays an important role in the rehabilitation for spinal cord injured individuals, and exoskeleton can assist with this process. In this paper, a self-balancing exoskeleton robot is introduced, which can provide assist not only in gait training, but also in balance training. In addition, it allows individuals walk with it without other assistive devices. This exoskeleton is designed to have a high degree of compatibility with humans. The structure and control system of the exoskeleton is introduced and the forward and inverse kinematic are solved, which enables the robot to perform various rehabilitation training actions as required. Experiments with a male subject have shown that this exoskeleton achieves the predicted results in gait training and balance training.

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Dynamic modeling and vibration analysis of a 6-DOFs industrial robot considering joint flexibility

Dynamic modeling and vibration analysis of a 6-DOFs industri...

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

作者： Shen, Guodong Xu, Sheng Chen, Chunjie Wang, Qiang Shandong Institute of Advanced Technology Chinese Academy of Sciences Shandong Jinan250102 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China

ISBN: (纸本)9781665436786

For the industrial robots, the vibration caused by the joint flexibility could affect the manipulator's performance significantly. Therefore, the modeling and vibration analysis of industrial robot considering joint flexibility has become an important topic in recent years. However, the research on flexible-joint manipulator is usually performed for planar robots, whereas the research on general spatial multi degrees of freedom (DOFs) industrial robots are still limited. In this paper, the dynamic modeling approach is developed for vibration analysis of the serial industrial robot having six DOFs. Firstly, based on the Spong's model of joint deformation, the flexibility of all joints is considered concurrently, and the partial velocity relationship between each link and the joint are deduced. Then, the dynamic model of the 6-DOFs flexible robot is derived according to the Kane equation. The results using the proposed Kane-based method are verified by several numerical simulations. Finally, vibration responses of the end-effector under different joint stiffness parameters are analyzed. The results in this study can offer some useful guidance for the path planning and control to suppress the vibration of the multi-DOFs industrial robots. © 2021 IEEE.

关键词： Vibration analysis

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A data-driven shared control system for exoskeleton rehabilitation robot

A data-driven shared control system for exoskeleton rehabili...

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

作者： Li, Feng He, Yong Li, Jinke Ni, Jiangpeng Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9781665436786

It is very important to establish a control operating system for rehabilitation robots, especially to improve the rehabilitation effect and human-machine interaction ability of patients. Exoskeletons have been proved to be effective in providing highly repeatable and accurate rehabilitation exercises, but most existing exoskeletons have inconsistent operating systems and data loss. This paper designed a novel data-driven shared control system(DDSCS) farmework, applied to different exoskeleton rehabilitation robots (ERR). Due to the unique physical characteristics of exoskeleton rehabilitation robots, it can't be adapt to different patients. Firstly, the DDSCS framework is established via the data-driven and shared technology, and the feasibility is analyzed. Secondly, to iterate the individualized gait trajectory, data-driven gait trajectory correction model is designed. Finally, the shared human-machine interface is developed, and the superiority and effectiveness of DDSCS framework are verified by the exoskeleton robot experiments. © 2021 IEEE.

关键词： Control systems

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