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

作者： Zhang, Liyuan Peng, Yige Qi, Xiaoxuan Bao, Sheng Yuan, Jianjun Shanghai Ic Technology & Industry Promotion Center Shanghai210203 China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai200444 China

ISBN: (纸本)9798350355154

This paper presents the research status of rehabilitation robot in detail. In order to understand the current situation of rehabilitation robots, they are divided into four categories, such as upper limb rehabilitation robots, lower limb rehabilitation robots, massage assistance robots and other rehabilitation robots. The research status and existing problems of rehabilitation robots at home and abroad in recent years are introduced in detail, and the functions of rehabilitation robots are demonstrated. Trained upper limb rehabilitation robots and lower limb rehabilitation robots have been introduced, which help patients undergo rehabilitation training and demonstrate strong recovery functions. Massage auxiliary robots provide continuous and stable massage therapy to the patient's specific muscle tissue, relieving the patient's pain. Thermal moxibustion robots and acupuncture robots provide rehabilitation treatment for patients in the way of traditional Chinese medicine. Finally, the common challenges in the research field of rehabilitation robots are discussed, and the future development trends of various rehabilitation robots are proposed. © 2024 IEEE.

关键词： Acupuncture

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T3SFNet: A Tuned Topological Temporal-Spatial Fusion Network for Motor Imagery with Rehabilitation Exoskeleton 7th

T3SFNet: A Tuned Topological Temporal-Spatial Fusion Network...

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7th International Conference on Cognitive Systems and Information Processing, ICCSIP 2022

作者： Shi, Kecheng Mu, Fengjun Zou, Chaobin Qin, Yizhe Peng, Zhinan Huang, Rui Cheng, Hong Center for Robotics School of Automation Engineering University of Electronic Science and Technology of China Chengdu China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9789819906161

In recent years, motor imagery-based brain computer interfaces (MI-BCI) combined with exoskeleton robot has proved to be a promising method for spinal cord injury (SCI) rehabilitation training. The core of BCI is to achieve a high accurate movement prediction based on patient’s MI. The inconsistent response frequency of MI in different trials and subjects leads to the limited performance accuracy of MI movement prediction method for the single subject. The individual differences in the activation patterns of MI brain regions bring a greater challenge to the generalization ability of the method. According to the MI mechanism, this paper proposes a graph-based tuned topological temporal-spatial fusion network (T3SFNet) for MI electroencephalography (MI-EEG) limb movement prediction. The proposed method designs a learnable EEG tuning mechanism to fuse and enhance the subject’s MI response band data, and then uses a channel node-based graph convolutional network and a temporal-spatial fusion convolutional network to extract the topological features and spatiotemporal coupling features of the fused band data respectively. We evaluate the proposed approach on two MI datasets and show that our method outperforms state-of-the-art methods in both within-subject and cross-subject situations. Furthermore, our method shows surprising results on the small-sample migration test, reaching the prediction baseline with only of the data sample size. Ablation experiments of the model demonstrate the effectiveness and necessity of the proposed framework. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electroencephalography

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Localization of Mobile Robot Aided for Large-Scale Construction Based on Optimized Artificial Landmark Map in Ongoing Scene

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Computer Modeling in engineering & Sciences 2022年第3期130卷 1853-1882页

作者： Zhen Xu Shuai Guo Tao Song Yuwen Li Lingdong Zeng Shanghai Key Laboratory of IntelligentManufacturing and Robotics School of Mechatronic Engineering and AutomationShanghai UniversityShanghai200444China National Demonstration Center for Experimental Engineering Training Education Shanghai UniversityShanghai200444China

The effectiveness of mobile robot aided for architectural construction depends strongly on its accurate localization *** of mobile robot is increasingly important for the printing of buildings in the construction *** many available studies on the localization have been conducted,only a few studies have addressed the more challenging problem of localization for mobile robot in large-scale ongoing and featureless *** realize the accurate localization of mobile robot in designated stations,we build an artificial landmark map and propose a novel nonlinear optimization algorithm based on graphs to reduce the uncertainty of the whole ***,the performances of localization for mobile robot based on the original and optimized map are compared and ***,experimental results show that the average absolute localization errors that adopted the proposed algorithm is reduced by about 21%compared to that of the original map.

关键词： Large-scale construction artificial landmark map localization mobile robot non-linear optimization

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BLE beacons for sample position estimation in a life science automation laboratory

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Transportation Safety and Environment 2024年第3期6卷 111-123页

作者： Haiping Wu Steffen Junginger Thomas Roddelkopf Hui Liu Kerstin Thurow Institute of Artificial Intelligence&Robotics(IAIR) Key Laboratory of Traffic Safety on Track of Ministry of EducationSchool of Traffic and Transportation EngineeringCentral South UniversityChangsha 410075HunanChina Institute of Automation(IAT) University of Rostock18119 RostockGermany Center of Life Science Automation(celisca) University of Rostock18119 RostockGermany

Estimation of the sample position is essential for working process monitoring and management in the life science automation lab*** low-energy(BLE)beacons have the advantages of low price,small size and low energy consumption,which make them a promising solution for sample position estimation in the automated *** fingerprinting models have been proposed to achieve indoor localization with the received signal strength(RSS)***,most of the research depends on intensive beacon *** estimation,which depends entirely on one beacon,is more suitable for sample position estimation in large automated *** complexity of the life science automation laboratory environment brings challenges to the traditional path loss model(PLM),which is a widely used radio wave propagation model-based proximity estimation *** this paper,BLE sensing devices for sample position estimation are *** BLE beacon-based proximity estimation is discussed in the framework of machine learning,in which the support vector regression(SVR)is utilized to model the nonlinear relationship between the RSS data and distance,and the Kalman filter is utilized to decrease the RSS data *** experimental results over different environments indicate that the SVR outperforms the PLM significantly,and provides 1 m absolute errors for more than 95%of the testing *** Kalman filter brings benefits to stable distance *** from proximity-based sample position estimation,the proposed framework turned out to be effective in position estimation between parallel workbenches and position estimation on an automated workstation.

关键词： BLE beacon position estimation proximity estimation received signal strength(RSS) support vector regression(SVR) life science automation laboratory

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BLE beacon-based floor detection for mobile robots in a multi-floor automation laboratory

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Transportation Safety and Environment 2024年第2期6卷 114-121页

作者： Haiping Wu Hui Liu Thomas Roddelkopf Kerstin Thurow Institute of Artificial Intelligence&Robotics(IAIR) Key Laboratory of Traffic Safety on Track of Ministry of EducationSchool of Traffic and Transportation EngineeringCentral South UniversityChangshaHunan 410075China Center of Life Science Automation(celisca) 18119 Rostoc kGerman y Institute of Automation(IAT) University Rostock18119 RostockGermany

As an important task of multi-floor localization,floor detection has elicited great *** infrastructures like Wi-Fi and Bluetooth Low Energy(BLE)play important roles in floor ***,most floor detection research tends to focus on data modelling but pays little attention to the data collection system,which is the basis of wireless infrastructure-based floor *** fact,the floor detection task can be greatly simplified with proper data collection system *** this paper,a floor detection solution is developed in a multi-floor life science automation lab.A data collection system consisting of BLE beacons,a receiver node and an Internet of Things(IoT)cloud is *** features of the BLE beacon under different settings are evaluated in detail.A mean filter is designed to deal with the fluctuation of the received signal strength indicator data.A simple floor detection method without a training process was implemented and evaluated in more than 100 floor detection *** time delay and floor detection accuracy under different settings are ***,floor detection is evaluated on the H20 multi-floor transportation *** sensor nodes are installed on the robot at different *** floor detection performance with different installation heights is *** experimental results indicate that the proposed floor detection method provides floor detection accuracy of 0.9877 to 1 with a time delay of 5s.

关键词： BLE beacon floor detection multi-floor automation transportation robot

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A policy gradient algorithm integrating long and short-term rewards for soft continuum arm control

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Science China(Technological Sciences) 2022年第10期65卷 2409-2419页

作者： DONG Xiang ZHANG Jing CHENG Long XU WenJun SU Hang MEI Tao School of Electrical Engineering and Automation Anhui UniversityHefei 230601China State Key Laboratory for Control and Management of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Robotics Research Center Peng Cheng LaboratoryShenzhen 518055China

The soft continuum arm has extensive application in industrial production and human life due to its superior safety and flexibility. Reinforcement learning is a powerful technique for solving soft arm continuous control problems, which can learn an effective control policy with an unknown system model. However, it is often affected by the high sample complexity and requires huge amounts of data to train, which limits its effectiveness in soft arm control. An improved policy gradient method, policy gradient integrating long and short-term rewards denoted as PGLS, is proposed in this paper to overcome this issue. The shortterm rewards provide more dynamic-aware exploration directions for policy learning and improve the exploration efficiency of the algorithm. PGLS can be integrated into current policy gradient algorithms, such as deep deterministic policy gradient(DDPG). The overall control framework is realized and demonstrated in a dynamics simulation environment. Simulation results show that this approach can effectively control the soft arm to reach and track the targets. Compared with DDPG and other model-free reinforcement learning algorithms, the proposed PGLS algorithm has a great improvement in convergence speed and performance. In addition, a fluid-driven soft manipulator is designed and fabricated in this paper, which can verify the proposed PGLS algorithm in real experiments in the future.

关键词： soft arm control Cosserat rod deep reinforcement learning policy gradient algorithm high sample complexity

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Research on Robot Path Planning Algorithm for Filter Plate Cleaning of Plate and Frame Filter Press 4

Research on Robot Path Planning Algorithm for Filter Plate C...

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4th International Symposium on Artificial Intelligence and Intelligent Manufacturing, AIIM 2024

作者： Xu, Jie Cui, Long Zhao, Yongguo Tian, Xincheng Center for Robotics School of Control Science and Engineering Shandong University Jinan China Engineering Research Center of Intelligent Unmanned System Ministry of Education Jinan China Institute of Automation Qilu University of Technology Shandong Academy of Sciences Jinan China

ISBN: (纸本)9798331541729

Plate and frame filter press is an important solid-liquid separation equipment that plays an important role in many fields. The filter plate is one of the core components of the frame filter press, and its main function is to support the filter cloth and form a filter chamber. After the filtration process of the filter press is completed, a large number of impurities are often attached to the filter plate, so it is of great value to study the impurity cleaning problem of the filter plate of the plate and frame filter press. In this paper, aiming at the cleaning process of the filter plate of the plate and frame filter press, the image information of the filter plate is obtained by visual means, and then the image is analyzed and processed to obtain the position information of the impurities of the filter plate, the path planning of the obtained position information is carried out, and finally the robot is made to complete the cleaning task efficiently and accurately according to the planned path, which has certain practical value. © 2024 IEEE.

关键词： Robot programming

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Editorial:special issue on frontiers of control and automation,dedicated to *** *** 60th birthday

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Control Theory and Technology 2023年第3期21卷 263-264页

作者： Jie Chen Jie Huang Lihua Xie Department of Control Science and Engineering Tongji UniversityShanghaiChina Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong KongChina Center for Advanced Robotics Technology Innovation School of Electrical and Electronic EngineeringNanyang Technological UniversitySingaporeSingapore

It is our great pleasure and honor to organize this special issue"Frontiers of Control and automation"in honor of the 60th birthday of our long-time colleague and friend Professor Ben *** Chen obtained his *** in mathemat-ics and computer science in 1983 from Xiamen University,China;*** in electrical engineering in 1988 from Gonzaga University,Spokane,Washington,USA;and *** in electrical and computer engineering in 1991 from Washington State University,Pullman,Washington,USA.

关键词： computer Xiamen frontier

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Analysis of Multi-AGVs Management System and Key Issues: A Review

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Computer Modeling in engineering & Sciences 2022年第6期131卷 1197-1227页

作者： Wenhao Lu Shuai Guo Tao Song Yuwen Li Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and AutomationShanghai UniversityShanghai200444China National Demonstration Center for Experimental Engineering Training Education Shanghai UniversityShanghai200444China

Multiple Automatic Guided Vehicle(multi-AGVs)management systems provide an effective solution to ensuring stable operations of multi-AGVs in the same scenario,such as flexible manufacturing systems,warehouses,container terminals,*** type of systems need to balance the relationship among the resources of the system and solve the problems existing in the operation to make the system in line with the requirement of the *** multi-AGVs management problem is a multi-objective,multi-constraint combinatorial optimization problem,which depends on the types of application *** article classifies and compares the research papers on multi-AGVs management in ***,according to the different dimensions of the problem,the multi-AGVs management system is analyzed from three perspectives,namely,1)task dimensiondispatch,2)spatial dimension-path,and 3)time *** detailed comparison between the three dimensions and their respective solutions are discussed in detail as ***,according to their utility,the multi-AGVs management problems are divided into three categories:1)cost reduction,resource-oriented,2)efficiency improvement,problem-oriented,3)personalized demand,*** algorithm and methods of the different utility-oriented are analyzed and *** related literature is summarized and corresponds to the composition of the multi-AGVs management system and the multi-AGVs management ***,according to the literature review,suggestions are made for further research.

关键词： Multiple automatic guided vehicle dispatch route schedule

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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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