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ViT-based Terrain Recognition system for wearable soft exosuit

Biomimetic intelligence & Robotics 2023年第1期3卷 57-64页

作者： Fangliang Yang Chunjie Chen Zhuo Wang Hui Chen Yao Liu Gang Li Xinyu Wua Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China Shenzhen College of Advanced Technology University of Chinese Academy of SciencesShenzhen 518055China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Guangdong-Hong Kong-Macao Joint Laboratory of Human–Machine Intelligence-Synergy Systems Shenzhen 518055China SIASUN Robot and Automation CO. LtdShenyang 110169China

Terrain classification and force assistance strategies in complex environments have always piqued the interest of many *** wearable soft exosuits,inaccurate terrain recognition can easily introduce undesired assist forces that can easily injure the *** of these problems,we introduced a depth camera into the exosuit system,perform classification of terrain based on a Vision Transformer(ViT),and optimized the control algorithm,which is known as a ViT-Based Terrain Recognition system(TTRS).First,we used the Transformer algorithm to achieve a considerable classification effect in terrain *** also introduced terrain recognition as prior knowledge into the force assistance strategy of the exosuit,providing different force assistance to the exosuit in different ***,we performed human experiments with seven able-bodied people(six males and one female).The promising results demonstrate that our classification accuracy can reach 99.2%under six different terrains and that it can smoothly switch the force–assist curve in different terrains to better adapt to the complex terrain and improve the walking *** aforementioned terrain recognition algorithms and force–assist strategies may positively influence the study of soft exosuit,powered prostheses,and orthotics.

关键词： Vision Transformer(ViT) Depth camera Wearable soft exosuit Force assistance strategy Terrain recognition

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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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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Wang, Zhuo Chen, Hui Yang, Fangliang Wang, Xiangyang Wu, Xinyu Chen, Chunjie Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781665481090

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 (R2) 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, ρ, and R2 of 3.09± 0.90,\ 0.9911 ± 0.0052, and 0.9817± 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. © 2024 IEEE.

关键词： Clinical research

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PREDICTIVE control OF GREENHOUSE TEMPERATURE BASED ON MIXED LOGICAL DYNAMICAL systemS

PREDICTIVE CONTROL OF GREENHOUSE TEMPERATURE BASED ON MIXED ...

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World Automation Congress 2010

作者： LINLIN QIN CHUN SHI QING LING GANG WU JUN WANG XIAOJUN QIAO Department of Automation University of Science and Technology of China Machine Vision and Intelligence Control Technology Key Laboratory Hefei University National Engineering Research Center for Information Technology in Agriculture

Most of the greenhouse climate control equipments in China are on-off control and without displacement ***,modeling and control theories based on continuous control devices are not *** the other hand,conventional on-off control algorithms require frequent switch actions of equipments,which leads to equipment spoilage and energy *** address these issues,this paper proposes to control greenhouse climate using a hybrid system *** the interactive dynamics between the actions of ventilation window and the output of the control system（temperature）according to the value of inside temperature and operational constrains,the ventilation window temperature system in a greenhouse can be regarded as a hybrid dynamical *** addition to building models of greenhouse temperature,a model predictive control（MFC）algorithm of greenhouse air temperature is proposed for the mixed logical dynamical *** results in a greenhouse prove the effectiveness of our modeling and control algorithms.

关键词： air temperature system greenhouse hybrid systems mixed logical dynamical（MLD） systems model predictive control（MPC）

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Distributed Attack Detection of Multi-area Power systems Against False Data Injection Attacks

Distributed Attack Detection of Multi-area Power Systems Aga...

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第43届中国控制会议

作者： Kecheng Li Genyuan Yang Shanling Dong Meiqin Liu College of Control Science and Engineering Zhejiang University College of Electrical Engineering Zhejiang University the National Key Laboratory of Human-Machine Hybrid Augmented Intelligence Xi'an Jiaotong University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The increasing integration of smart grid technologies in multiregional power systems improves efficiency but also exposes them to cyber security threats,especially false data injection *** this paper,we address this challenge by proposing a distributed detection framework tailored for multi-regional power *** centralized approaches are insufficient to cope with the dynamic and decentralized nature of these *** framework aims to simultaneously monitor and analyze multiple regions in real-time,enhancing the system's ability to withstand false data injection *** study outlines the proposed framework and provides simulation results for validation,emphasizing the need for proactive defense mechanisms in safeguarding the data integrity of power systems.

关键词： multi-area power systems false data injection attacks distributed detection framework

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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IEEE International Conference on systems, Man and Cybernetics

作者： Ruijie Xu Shichao Chen Wenqiao Sun Yisheng Lv Jialiang Luo Ying Tang The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems The Center of National Railway Intelligent Transportation System Engineering and Technology Institute of Automation Chinese Academy of Sciences China Academy of Railway Sciences Corporation Limited Beijing China China Academy of Railway Sciences Corporation Limited Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing Beijing China Department of Electrical and Computer Engineering Rowan University Glassboro USA

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation system (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance.

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Modeling Based on MOGA and the Dynamic ε -SVM for Fermentation Process

Modeling Based on MOGA and the Dynamic ε -SVM for Fermentat...

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World Congress on Intelligent control and Automation (WCICA)

作者： Xuejin Gao Pu Wang Chongzheng Sun Yating Zhang Huiqing Zhang Jianqiang Yi College of Electronic Information and Control Engineering Beijing University of Technology Beijing China The Key Laboratory of Complex System and Intelligence Science Chinese Academy and Sciences Beijing China

To found the suitable models to describe the behavior of biochemistry systems, the dynamic epsiv-SVM method was proposed on the basis of SVM. Each training sample uses different error. The existed methods for selecting the parameters of SVM not only consume time, but also are difficult to find the optimal parameters. The optimal parameters were automatically decided by using multi-object genetic algorithm (MOGA). A new modeling method that combined MOGA with the dynamic epsiv-SVM was presented. The model for penicillin titer pre-estimate was developed by it in Matlab 6.5 with data collected from real plant. The model possesses the strong capability of fitting and generalization. Experiments show that the dynamic epsiv-SVM is superior to the standard SVM modeling method. MOGA is very feasible and efficient too

关键词： Mathematical model Support vector machines Artificial neural networks Risk management Educational programs systems engineering education Genetic algorithms Computer languages Sun Educational institutions

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Stochastic stability analysis and control of networked control systems with randomly varying long time-delays

Stochastic stability analysis and control of networked contr...

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World Congress on Intelligent control and Automation (WCICA)

作者： Yuequan Yang De Xu Min Tan Xianzhong Dai Key Laboratory of Complex System and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China Department of Automatic Control South-East University Nanjing China

ISBN: (纸本)0780382730

This paper mainly studies stability and optimal control for networked control systems with the real-time setup of time-driven sensor, event-driven controller and actuator, and with the assumption that network-induced delay is no longer than certain known times of sampling period. The modeling of this class of networked control systems is given. Then, preliminary stochastic stability analysis of it is presented. Finally, based on stochastic optimal control theory an LQG control scheme is provided. Much work needs to be continued for future research.

关键词： Stochastic systems Stability analysis control systems Networked control systems Optimal control Stochastic processes Real time systems Sensor systems Actuators Sampling methods

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Admittance control based Hemiplegic Exoskeleton Motion control

Admittance Control based Hemiplegic Exoskeleton Motion Contr...

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2022 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2022

作者： He, Bailin Zhou, Xin Huai, Yaping Liu, Jiaqing Li, Pengbo Wang, Can Wu, Xinyu Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Department of Rehabilitation Medicine Shenzhen Longhua District Central Hospital Shenzhen518000 China

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

In this paper, a method based on admittance control is developed to improve patients' comfort wearing an exoskeleton robot for rehabilitation training. In our previous work, we designed a modular and convenient hemiplegic exoskeleton robot. The mechanical structure will cause stiffness when it comes to contact with the human body in practical applications. We introduced admittance control to improve the flexibility of the exoskeleton robot and improve the subjects' comfort. This paper considers coupling of model between the exoskeleton and the human body as the human-computer interaction force of the system at the main human-computer interaction point. Measuring the interaction force between exoskeleton members and limbs, the work uses the virtual admittance model to correct the system's inherent characteristics and studies the control method's stability with Lyapunov's theory. The experiment collected the subject movement information which was converted the movement information of the exoskeleton. Human-computer interaction forces in the thigh and calf were measured while the exoskeleton assisted the subject's movement. The experimental results show that adding the admittance controller reduces the human-computer interaction force from 5g to 2g and 6g to 3g, respectively. © 2022 IEEE.

关键词： Human computer interaction

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One-Iteration-per-Update 94LVI Algorithm Solving Time-Varying Quadratic Programming in Real Time with Numerical and Graphical Results

One-Iteration-per-Update 94LVI Algorithm Solving Time-Varyin...

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第34届中国控制与决策会议

作者： Yunong Zhang Zhiwen Yuan Tangke Xu School of Computer Science and Engineering Sun Yat-sen University Guangdong Key Laboratory of Modern Control Technology Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Research Institute of Sun Yat-sen University in Shenzhen

Recently,there have been many methods to solve quadratic programming(QP) *** this work,on the basis of linear variational inequality(LVI),a simple and effective algorithmic method(i.e.,one-iteration-per-update 94 LVI algorithm)is proposed for solving the time-varying QP problem,which is subject to time-varying linear equality,inequality and bound constraints at the same *** that the normal 94 LVI algorithm is usually used to find the optimal solution of the static QP problem in the ***,we transform the QP problem into a piecewise-linear projection equation(PLPE).Then,the continuous time-varying QP problem is divided into many static QP problems via sampling time interval ***,we use the normal 94 LVI algorithm to update with only one iteration based on the solution of previous sampling time instant,and finally we get the solution of each sampling time *** numerical experiments,as a novel approach,the one-iterationper-update 94 LVI is able to get the solution of each sampling time instant much quickly and quite accurately when solving the time-varying QP problem.

关键词： time-varying QP problem linear variational inequality piecewise-linear projection equation one-iteration-perupdate 94LVI numerical algorithm

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Bat algorithm with oscillation element

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International Journal of Innovative Computing and Applications 2015年第3-4期6卷 171-180页

作者： Cai, Xingjuan Li, Wuzhao Kang, Qi Wang, Lei Wu, Qidi Department of Control Science and Engineering Tongji University Shanghai201804 China Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology 030024 China Shanghai Key Laboratory of Financial Information Technology Shanghai200433 China

Bat algorithm is a novel swarm intelligent algorithm inspired by the echolocation behaviour of bats. However, the exploration capability is not well for some multi-model problems. In this paper, the control theory is applied to analyse the exploration behaviour for each bat, theoretical result shows the update manner in the standard version of bat algorithm can be viewed as a special case of oscillation element. Therefore, a new variant of bat algorithm, called bat algorithm with oscillation element, is designed. Different from the standard version, frequency is set to negative in this new variant. Furthermore, a new parameter, inertia weight is employed to provide a balance between exploitation and exploration. To test the performance, the CEC2013 shifted and rotated benchmark problems are used to compare, simulation results show our method is validity. Copyright © 2015 Inderscience Enterprises Ltd.

关键词： Benchmarking

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