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42nd Chinese Control Conference, CCC 2023

作者： Liu, Zezhi Fang, Yongchun Institute of Robotics and Automatic Information System Nankai University Tianjin300350 China Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China

ISBN: (纸本)9789887581543

In this paper, we propose a new method for using Dynamic Movement Primitives (DMPs) to enable robots to avoid volumetric obstacles when learning skills from human demonstrations. We can utilize coupling terms in DMPs to modify the planned trajectory of the end-effector. Our method combines superquadrics and a steering angle scheme to construct new coupling terms for obstacle avoidance, without relying on potential fields. This guarantees the convergence of the dynamic system. Additionally, we modify the original center point steering angle formula to improve the ability to avoid obstacles in a wider range of angles. Our proposed method is applicable to most types of superquadrics, including those with flat boundaries, and we validate it through simulations. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Collision avoidance

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Pressure Pain Recognition for Lower Limb Exoskeleton Robot with Physiological Signals 1

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2nd International Conference on Cognitive Computation and systems, ICCCS 2023

作者： Ma, Yue Wu, Xinyu Wang, Xiangyang Li, Jinke Qin, Pengjie Yin, Meng Cao, Wujing Yi, Zhengkun Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems Guangdong Shenzhen China Shandong Institute of Advanced Technology Chinese Academy of Sciences Shandong Jining China

ISBN: (数字)9789819708857

ISBN: (纸本)9789819708840

Pain is a feedback mechanism the body uses to protect itself. The perception of human pain is still missing in lower limb exoskeleton robots, such as the pain caused by the pressure between the knee joint and the baffle when the lower limb exoskeleton stands up, or the pain caused by the mismatch between the gait and the body function of the wearer when walking. Aiming at the pain perception problem of the exoskeleton robot, this study designed a pressure pain data acquisition paradigm combined first considering the movement mode of the exoskeleton robot, and collected facial electromyography and electrocardiography signals, as well as five levels of pain. Then a deep learning neural Network based on Temporal Convolutional Network and Long Short-Term Memory is designed. The composite Loss of Center Loss, InfoNEC Loss and Softmax Loss is designed. The designed deep neural network model was evaluated using the thermal pain dataset BioVid, and the average recognition rate using only electrocardiography signals reached 86.44%. By Using the fusion signals of electrocardiography, electrocardiogram and electromyogram signals, the average recognition accuracy can reach 87.16%, which is superior to other similar methods, and verifies the effectiveness of the proposed method. The proposed network is also used to verify the collected pressure pain dataset, and the recognition accuracy can reach 87.5%, which proves the validity of the collected data set. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electrocardiography

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Real-Time Gait Symmetry Enhancement in People with Unilateral Knee Injuries Using Deep Learning for Modulation of Knee Exoskeleton

Real-Time Gait Symmetry Enhancement in People with Unilatera...

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2023 International Conference on Design Science, ICDS 2023

作者： Wu, Xinyu Ma, Xiangyu Zhu, Aibin Mao, Han Wang, Xin Song, Jiyuan Institute of Robotics &Intelligent System Xi’an Jiaotong University Xi’an China School of Construction Mechinery Chang’an University Xi’an China

ISBN: (纸本)9798350343786

Gait rehabilitation is critical for postoperative rehabilitation to improve the quality of life in people with unilateral knee injuries. Although some studies have studied the effects of using rehabilitation exoskeletons for patients rehabilitation, the improvement of patient gait quality with a single knee exoskeleton has not been thoroughly investigated. In this study, a deep neural network-based biological torque controller is presented for real-time control of the unilateral knee exoskeleton. The aim was to improve the gait quality of patients by enhancing their gait symmetry. A lightweight unilateral knee exoskeleton system with low passive impedance and well transparent was used to develop and validate the controller during both treadmill and level walking modes. The proposed control strategy is characterized by accurate assisted output torque even when the motion pattern is changed, and does not require controller parameter adjustment. To test it, five able-bodied subjects used an exoskeleton with an artificial blocking device at the knee joint position that simulated the patient’ s defective postoperative pathological gait(i.e., reduced knee flexion). The subjects walked continuously on a treadmill and a flat surface. The experimental results demonstrated that the control strategy effectively improved the gait quality of the participants. © 2023 IEEE.

关键词： Exoskeleton (robotics)

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Squeezing More Past Knowledge for Online Class-Incremental Continual Learning

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 722-736页

作者： Da Yu Mingyi Zhang Mantian Li Fusheng Zha Junge Zhang Lining Sun Kaiqi Huang the State Key Laboratory of Robotics and System Harbin Institute of Technology(HIT)Harbin 150080China Center for Research on Intelligent System and Engineering Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Center for Research on Intelligent System and Engineering Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190the School of Artificial IntelligenceUniversity of Chinese Academy of SciencesBeijing 100049 the CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai 200031China IEEE

Continual learning(CL)studies the problem of learning to accumulate knowledge over time from a stream of data.A crucial challenge is that neural networks suffer from performance degradation on previously seen data,known as catastrophic forgetting,due to allowing parameter *** this work,we consider a more practical online class-incremental CL setting,where the model learns new samples in an online manner and may continuously experience new ***,prior knowledge is unavailable during training and *** works usually explore sample usages from a single dimension,which ignores a lot of valuable supervisory *** better tackle the setting,we propose a novel replay-based CL method,which leverages multi-level representations produced by the intermediate process of training samples for replay and strengthens supervision to consolidate previous ***,besides the previous raw samples,we store the corresponding logits and features in the ***,to imitate the prediction of the past model,we construct extra constraints by leveraging multi-level information stored in the *** the same number of samples for replay,our method can use more past knowledge to prevent *** conduct extensive evaluations on several popular CL datasets,and experiments show that our method consistently outperforms state-of-the-art methods with various sizes of episodic *** further provide a detailed analysis of these results and demonstrate that our method is more viable in practical scenarios.

关键词： Catastrophic forgetting class-incremental learning continual learning(CL) experience replay

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Genetic Algorithm-Based Optimization of the Rolling-Contact Involute Robot Joints 11

Genetic Algorithm-Based Optimization of the Rolling-Contact ...

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11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023

作者： Liang, Renghao Zhang, Zhuying Yang, Wenlin Zhang, Qifeng Guangdong Institute of Intelligent Unmanned System Guangdong China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350333664

The hand exoskeleton has been widely studied in the fields of hand rehabilitation and grasping assistance tasks. Current hand exoskeletons face challenges in combining a user-friendly design with a lightweight structure and accurate modeling of hand motion. In our previous research work, we proposed a pure rolling involute biomimetic joint for the design of hand exoskeletons, resulting in a portable structure with high biomimetic performance. However, in the optimization of the biomimetic joint, the optimization algorithm for the joint surface was not intelligent enough, and several key parameters were manually adjusted, leading to suboptimal parameters obtained from the optimization process. Therefore, in this paper, we propose using genetic algorithms to optimize the parameters of the joint surface, aiming to achieve a joint with higher motion biomimetic performance. The optimization method presented in this paper not only improves the optimization effectiveness of the biomimetic joint but also provides new insights into multi-parameter optimization for other biomimetic joints. © 2023 IEEE.

关键词： biomimetic joint exoskeleton genetic algorithms intelligent robots

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RTHG: Towards Real- Time Head Detection and Gaze Estimation

RTHG: Towards Real- Time Head Detection and Gaze Estimation

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Zhao, Kunxu Hu, Zhengxi Zhang, Qianyi Liu, Jingtai Institute of Robotics and Automatic Information System Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin300350 China

ISBN: (纸本)9781665481090

As an important way of understanding human in-tentions, gaze estimation has always been a research hotspot in the field of human-robot interaction. Most studies now estimate gaze direction by analyzing head features and head detection is required before gaze estimation. For these two sequential tasks, the current research usually adopts two different networks, which increases the memory occupation of the graphics card and is not easy to deploy on the edge device. In this paper, we propose a unified network for simultaneous head detection and gaze estimation, unifying these two tasks into a multi-task learning model. In this network framework, head detection and gaze estimation share the same set of features, which enables them to promote each other to improve detection accuracy. We evaluated our model on gaze360 dataset and the gaze error dropped to 19.62 degrees while running at 23 fps. © 2022 IEEE.

关键词： Human robot interaction

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Design and Evaluation of a Self-Aligning Knee Exoskeleton for Knee Extension Assistance during Walking 37

Design and Evaluation of a Self-Aligning Knee Exoskeleton fo...

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37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022

作者： Liu, Zhaoyuan Yin, Weihao Han, Jianda Zhang, Juanjuan Institute of Robotics and Automatic Information System Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China

ISBN: (纸本)9781665465366

Exoskeletons can help people with impaired knee extensor function by providing assistance. Previous studies have shown that adding passive degrees of freedom to the knee exoskeleton can help reduce unwanted load on the knee joint. However, the problem of achieving passive degrees of freedom with low-weight structures has not been resolved. We designed and built a self-aligning knee exoskeleton which weighs 1.76kg and uses a slider-rail structure to add a passive degrees of freedom in the kinematic chain. The device was actuated by an off board motor to apply knee extension assist torque during walking. A magnetic connection device was designed to quickly connect the thigh and calf segments of the exoskeleton. The exoskeleton was evaluated on a healthy subject walking uphill at 0°, 2°, 4° and 6° slope with a setup assistance profile. The results indicated a decrease in rectus femoris, vastus medialis and vastus lateralis activity under assistance. The root mean squared (RMS) of the vastus medialis muscle activity decreased 21%, 25%, 24%, and 33% in each of the four conditions. These preliminary results show that the device has the capability to explore more assistance strategies to improve gait rehabilitation. © 2022 IEEE.

关键词： Degrees of freedom (mechanics)

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Gait recognition based on sEMG and Deep Residual Shrinkage Network

Gait recognition based on sEMG and Deep Residual Shrinkage N...

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

作者： Luo, Mingxiang Yang, Lijun Sun, Zeyu Yin, Meng Ma, Yue Wu, Xinyu Cao, Wujing Chinese Academy of Sciences and Southern University of Science and Technology Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518005 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Siat Branch China University of Birmingham United Kingdom

ISBN: (纸本)9798350327182

Transverse resistance exoskeleton is expected to provide better rehabilitation training methods for patients with lower limb injury. Lateral walking gait recognition plays an important role in lateral resistance exoskeleton control. In the phase of lateral walking out of synchrony, the EMG signals produced by the thighs will be different. The EMG signals collected by five subjects while walking laterally were used in the experiment. The four muscles are: the gluteus medius of the left leg, the tensor fascia lata, the adductor major, and the tensor fascia lata of the right leg. Based on the one-dimensional EMG signals of the four muscles, this paper uses the classification model commonly used in the MATLAB toolbox for training and recognition. However, the experimental results show that TREE and KNN have poor recognition accuracy for the four gait stages. To this end, this paper applies the convolutional residual shrinkage network (DRSN) to this occasion. The collected one-dimensional EMG signals are plotted as pictures and fed into the model for training and classification. Experimental results show that the classification accuracy is greatly improved compared with the previous model. © 2023 IEEE.

关键词： Muscle

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Evaluation of a Bionic Cable-driven Ankle Exoskeleton system for Human Walking Assistance 37

Evaluation of a Bionic Cable-driven Ankle Exoskeleton System...

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37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022

作者： Yin, Weihao Wang, Wei Ding, Jianquan Liu, Jingtai Zhang, Juanjuan Tianjin Key Laboratory of Intelligent Robotics Institute of Robotics and Automatic Information System Nankai University Tianjin300350 China

ISBN: (纸本)9781665465366

In order to further explore the performance of assistive exoskeleton, we tested and evaluated a bionic cable-driven ankle exoskeleton system for human walking assistance in this paper. A bionic ankle exoskeleton was used as an end-effector to provide many different patterns of assistance. Assistive forces were transmitted by a flexible Bowden cable which attached fewer moments of inertia to the wearer and minimized the impact of wearable devices on the wearer's natural movements. We preset the assistive torque trajectory according to biological ankle moment during walking and used a torque control method of proportional control with damping injection compensated by adaptive iterative learning to achieve high-performance torque control. We evaluated the kinematics and biological efforts of one subject with predefined assistance patterns. Assistance during walking on a treadmill reduced the metabolic cost by 10.34% compared with normal shoes. The root mean square (RMS) of the soleus muscle activity decreased by 52.2%, and ankle joint moment reduced by 40.4% with the same pattern. The experimental results show that the device is capable of improving walking economy. © 2022 IEEE.

关键词： Wearable technology

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Reliable observer-based control against sensor failures for fractional order systems 41

Reliable observer-based control against sensor failures for ...

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第41届中国控制会议

作者： Bingxin Li Xiangfei Zhao Yaowei Liu Xin Zhao Institute of Robotics and Automatic Information System and the Tianjin Key Laboratory of Intelligent Robotics Nankai University Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In the paper,the state and sensor failure observer for fractional order systems with order 0 <α <1 and 1 <α<2 is proposed to estimate the system state and sensor failures at the same *** general,unbounded sensor faults will inevitably lead to system ***,it is very necessary to study the reliable controller for fractional order systems against sensor *** the linear matrix inequality concept and the augmented system method,the sensor faults can be in any form,even unbounded.A reliable observer-based controller based on the state and sensor failures estimation is proposed,which can make the system work well regardless of whether the sensor *** α=1,methods proposed in the paper are equivalent to these of the integer order systems,scilicet,our methods can be extended to integer order ***,a simulation example is used to demonstrate the efficiency of the present methods.

关键词： Fractional order systems state and sensor failures linear matrix inequality reliable observer-based controller

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