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arXiv 2023年

作者： Jiao, Yang Yang, Kai Wu, Tiancheng Jian, Chengtao Huang, Jianwei Department of Computer Science and Technology Tongji University China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University China Shanghai Research Institute for Intelligent Autonomous Systems China School of Science and Engineering The Chinese University of Hong Kong Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society China

Trilevel learning, also called trilevel optimization (TLO), has been recognized as a powerful modelling tool for hierarchical decision process and widely applied in many machine learning applications, such as robust neural architecture search, hyperparameter optimization, and domain adaptation. Tackling TLO problems has presented a great challenge due to their nested decision-making structure. In addition, existing works on TLO face the following key challenges: 1) they all focus on the non-distributed setting, which may lead to privacy breach;2) they do not offer any non-asymptotic convergence analysis which characterizes how fast an algorithm converges. To address the aforementioned challenges, this paper proposes an asynchronous federated trilevel optimization method to solve TLO problems. The proposed method utilizes µ-cuts to construct a hyper-polyhedral approximation for the TLO problem and solve it in an asynchronous manner. We demonstrate that the proposed µ-cuts are applicable to not only convex functions but also a wide range of non-convex functions that meet the µ-weakly convex assumption. Furthermore, we theoretically analyze the non-asymptotic convergence rate for the proposed method by showing its iteration complexity to obtain ϵ-stationary point is upper bounded by (Formula Presented). Extensive experiments on real-world datasets have been conducted to elucidate the superiority of the proposed method, e.g., it has a faster convergence rate with a maximum acceleration of approximately 80%. Copyright © 2023, The Authors. All rights reserved.

关键词： Decision making

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Control-Oriented Modeling of a Soft Manipulator Using the Learning-Based Koopman Operator

Control-Oriented Modeling of a Soft Manipulator Using the Le...

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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Jie Chen Yu Dang Weiguang Huo Ningbo Yu Jianda Han College of Artificial Intelligence Nankai University Tianjin China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China

Modeling the dynamics of soft manipulators remains challenging owing to their intrinsic compliance and nonlinear deformation. The Koopman operator theory provides a way to construct control-oriented linear models for soft robots. However, the modeling accuracy of the Koopman operator heavily depends on the choices of the eigenfunctions. In this paper, we propose a data-driven modeling framework for the soft manipulator using the learning-based Koopman operator (LKO). Distinct from the classical Koopman operator, the LKO leverages a neural network to discover the representations of the Koopman operator and the eigenfunctions. In this way, the LKO avoids the manual selection of eigenfunctions, enabling the identification of linear models with higher accuracy than that of the classical Koopman operator. The LKO was examined to predict the tip position and the configuration of a customized soft manipulator. Moreover, the LKO was compared with three conventional data-driven approaches, including the classical Koopman operator, feedforward neural network, and recurrent neural network. The results indicate that the modeling accuracy of the LKO was improved by over 60% compared with that of the other three conventional data-driven approaches. With the linear representation and high accuracy, the LKO has great potential to improve the model-based control performance of soft robots.

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Enhancing Robot Teleoperation in Remote Automation Production through an Event-Triggered Control Strategy

Enhancing Robot Teleoperation in Remote Automation Productio...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Mengke Wang Honghao Lv Ruohan Wang Haiteng Wu Lipeng Chen Yi Chen Haihui Yuan Geng Yang State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou China Zhejiang Key Laboratory of Intelligent Operation and Maintenance Robot Hangzhou Shenhao Technology Hangzhou China Robotics X Tencent Shenzhen China Intelligent Manufacturing Center DongFang Electric Corporation Academy of Science and Technology Co Chengdu China China South Industries Group Corporation Hangzhou Automation Research Insititute Co. Ltd. China State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Zhejiang Key Laboratory of Intelligent Operation and Maintenance Robot Hangzhou China

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

With the advancement of intelligent manufacturing, an increasing number of industrial production processes are transforming unmanned operations. This trend is particularly evident in factories that involve potential safety hazards, where the demand for unmanned production is becoming increasingly urgent. Teleoperation, as a core technology for achieving unmanned factories, holds tremendous importance in keeping workers safe from danger. However, traditional teleoperation strategies encounter challenges due to mismatches between master and slave workspaces, making it difficult to achieve both high precision and operation across large workspaces simultaneously. To address this issue, this paper proposes an event-triggered control strategy for a teleoperated robot system. By introducing a foot pedal as the event-triggered switch, the enablement and termination of teleoperation are associated with the activation of the pedal. Through resetting the start position, fine-grained teleoperation is achieved throughout the entire workspace of the robot. To demonstrate the advantages of the proposed control strategy, a mimicked wiring operation task scenario is constructed for experimental verification, and the teleoperation tasks are completed successfully and efficiently.

关键词： Wiring Accuracy Service robots Switches Market research Production facilities Main-secondary

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Functional Connectivity Analysis Revealed Abnormal Brain Network Pattern in Parkinson's Disease with Freezing of Gait

Functional Connectivity Analysis Revealed Abnormal Brain Net...

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Chinese Control Conference (CCC)

作者： Zhilin Shu Jinrui Liu Ting Song Jianda Han Ningbo Yu College of Artificial Intelligence Nankai University Tianjin China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China

Patients with Parkinson's disease (PD) commonly have deficits in lower-limb movements. Freezing of gait (FOG), a type of gait disturbance of PD, is a complex motor symptom exhibited as inability to generate an effective gait. The mechanism of lower-limb dysfunction of PD, especially FOG, remains to be explored. To investigate the neural mechanisms related to FOG in PD, we evaluated 39 subjects (13 PD patients with FOG, 13 PD patients without FOG, and 13 healthy subjects) based on electroencephalogram (EEG) signals while they performed the pedaling task. We conducted functional connectivity analysis using Magnitude Squared Coherence (MSC) and calculated the metrics to investigate the characteristics of the brain network among the three groups. The results indicated that PD patients were associated with reduced functional integration and segregation of brain network, subserving both motor and cognitive abilities. The reduced functional integration and segregation of cognitive processes were correlated with the severity of FOG. This study revealed the differences in brain networks between PD patients and healthy controls and provided insights into the neural mechanism of FOG.

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A Novel Surface Electromyography Signals Denoising Method for Gait Phase Classification

A Novel Surface Electromyography Signals Denoising Method fo...

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Chinese Control Conference (CCC)

作者： Yubo Sun Zhenhui Guo Yuxin Feng Ningbo Yu College of Artificial Intelligence Nankai University Tianjin China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China

Surface electromyography (sEMG) is a non-invasive technique for recording electrical activity and is extensively employed in gait phase classification. However, the measurement process of the sEMG signal inevitably introduces noise. Consequently, denoising is required for gait analysis from the collected sEMG signal. A novel denoising method ICEEMDAN-DFA-WD has been proposed in this paper. The sEMG signals were decomposed into several intrinsic mode functions (IMF) through an improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN). The Hurst exponents were simulated by detrended fluctuation analysis (DFA) to distinguish noisy IMF and desired IMF. During the walking process, the lower limbs' sEMG exhibits strong periodicity, and the desired IMF yields higher Hurst exponents than the noisy IMF. For the noisy IMF, noise removal was performed through further decomposition by wavelet transform, followed by a hard threshold. The processed IMFs were reconstructed to denoise sEMG. In this study, experiments were conducted to compare with the existing denoising methods WD, EMD-IIT, EEMD-IWT, VMD-SIT. The proposed method can obtain better denoising effect and gait phase classification accuracy. The proposed method provides a more effective way for sEMG denoising.

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Fundus-Image-Based Retinal Vascular Analysis in Myopic Eyes 42

Fundus-Image-Based Retinal Vascular Analysis in Myopic Eyes

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42nd Chinese Control Conference, CCC 2023

作者： Shen, Jichen Zou, Haohan Wang, Yan Liu, Jinchao Yu, Ningbo College of Artificial Intelligence Nankai University Tianjin300350 China Clinical College of Ophthalmology Tianjin Medical University Tianjin300070 China Tianjin Key Lab of Ophthalmology and Visual Science Tianjin Eye Institute Tianjin Eye Hospital Nankai University Affiliated Eye Hospital Tianjin300020 China Nankai University Eye Institute Nankai University Tianjin300350 China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin300350 China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China

ISBN: (纸本)9789887581543

Myopia is prevalent worldwide and it is of great significance to prevent, control and intervene myopia in an early stage. The etiopathogenesis of myopia remains unclear and needs further research. Fundus photographs can show biomarkers and lesions of the retina in a non-invasive way directly. To discover some potential changes in myopic eyes, we extracted the retinal vascular features from vessel segmented results, and calculated the Spearman correlation coefficients between the retinal vascular features and the spherical refractive errors. The Kruskal-Wallis test was applied to explore the difference exists in the characteristics of retinal vessels among the mild, moderate and high myopia groups. The statistical analysis results indicated that the higher the degrees of myopia, the smaller the retinal vessels. This study found vascular changes in myopic eyes through fundus images, which could help to explain the mechanism of myopia and the damage caused by myopia. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Ophthalmology

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Real-world Robot Reaching Skill Learning Based on Deep Reinforcement Learning

Real-world Robot Reaching Skill Learning Based on Deep Reinf...

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第32届中国控制与决策会议

作者： Naijun Liu Tao Lu Yinghao Cai Rui Wang Shuo Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology of the Chinese Academy of Sciences

Traditional programming method can achieve certain manipulation tasks with the assumption that robot environment is known and ***,with robots gradually applied in more domains,robots often encounter working scenes which are complicated,unpredictable,and *** overcome the limitation of traditional programming method,in this paper,we apply deep reinforcement learning(DRL) method to train robot agent to obtain skill *** policy trained with DRL on real-world robot is time-consuming and costly,we propose a novel and simple learning paradigm with the aim of training physical robot ***,our method train a virtual agent in an simulated environment to reach random target position from random initial ***,virtual agent trajectory sequence obtained with the trained policy,is transformed to real-world robot command with coordinate transformation to control robot performing reaching *** show that the proposed method can obtain self-adaptive reaching policy with low training cost,which is of great benefits for developing intelligent and robust robot manipulation skill system.

关键词： Robot reaching skill learning deep reinforcement learning

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HP-KPConv: Point Cloud Registration Evaluation via Local Feature Distribution Similarity

HP-KPConv: Point Cloud Registration Evaluation via Local Fea...

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IEEE International Conference on robotics and biomimetics

作者： Yaling Pan Li He Yisheng Guan Hong Zhang Ministry of Industry and Information Technology Key Laboratory of Quality and Reliability Engineering Technology of Civil Aircraft and Aero-Engine Chinese Electronic Product Reliability and Environmental Testing Research Institute Guangzhou China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China Biomimetic and Intelligent Robotics Lab (BIRL) Guangdong University of Technology Guangzhou China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

ICP is one of the most popular solutions for point cloud registration. However, the evaluation metric of the ICP algorithm, based on point-wise Euclidean distances, falls short in meeting the demands of high-precision alignment. In this paper, we propose a point cloud registration evaluation method based on local feature distribution to assess alignment quality, in particular the translation errors among matched point clouds. Rather than comparing the point-to-point Euclidean distance as adopted in ICP, our main idea is that the spatial distribution of one local region pre- and post-alignment should be similar. We design a filter to calculate local region similarity and find out outliers according to the similarity. This high-precision filter is integrated into the KPConv network, denoted as HP-KPConv. Finally, after conducting extensive experiments on Dingo robots and LiDAR, we validate the ability of HP-KPConv to effectively detect subtle alignment errors, proving its applicability in robot localization evaluations.

关键词： Point cloud compression Measurement Matched filters Graphical models Translation Robot localization Trajectory Quality assessment Robots Distribution functions

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An sEMG-based Hill-type Model for Estimation of Swallowing Motion

An sEMG-based Hill-type Model for Estimation of Swallowing M...

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IEEE International Conference on robotics and biomimetics

作者： Zhenhui Guo Yue Wang Song Zhang Jinqiao Wu Yang Yu Yu Dang Ningbo Yu Jialing Wu Jianda Han College of Artificial Intelligence Nankai University Tianjin China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China Tianjin Huanhu Hospital Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China Laboratory of Cerebral Vascular and Neurodegenerative Diseases Tianjin Neurosurgical Institute Tianjin Huanhu Hospital Tianjin China

ISBN: (纸本)9781665405362

Dysphagia is a common clinical symptom which can cause dehydration, malnutrition, pneumonia, and even death. Surface electromyography (sEMG) signals, which can be obtained in a non-invasive way, have been used for screening dysphagia, and estimation of the swallowing motion based on the sEMG signals is essential. In this paper, we propose an sEMG-based Hill-type model for estimation of swallowing motion. Firstly, the sEMG signals of suprahyoid and infrahyoid muscles and acceleration signals of larynx which represent the swallowing motion were collected simultaneously and preprocessed. Secondly, the relationship between the preprocessed sEMG signals and swallowing motion was established based on Hill-type muscle model and dynamics of larynx. Then experiments with four kinds of swallowing tasks were conducted to verify the proposed method. Analysis of the experimental results with normalized root-mean-square (NRMSE) and correlation coefficient (CC) verified the effectiveness of the proposed method.

关键词： Correlation coefficient Pulmonary diseases Conferences Dynamics Estimation Muscles Larynx

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Design of a Walking Assistive Robot Against Festination and Freezing of Gait

Design of a Walking Assistive Robot Against Festination and ...

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IEEE International Conference on robotics and biomimetics

作者： Yugen You Yuke Wang Weijia Hou Yang Yu Jianda Han Jialing Wu Ningbo Yu College of Artificial Intelligence Nankai University Tianjin China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China Tianjin Huanhu Hospital Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China Laboratory of Cerebral Vascular and Neurodegenerative Diseases Tianjin Neurosurgical Institute Tianjin Huanhu Hospital Tianjin China

ISBN: (纸本)9781665405362

Festination and freezing are typical and episodic gait disturbances of Parkinsonism, which constrain the life participation of patients. Gait training can reduce festination and freezing episodes by gait correction based on feedback and cueing-based walking. However, the training is normally restricted in clinical environment and it is tedious and labor-consuming for the therapists. To conduct in-home rehabilitation, safe solutions with feedback and cues rendering in real time to replace the therapists during training are expected. This paper describes a design of a walking assistive robot, which not only can give interactive feedback based on the abnormal gait detection, but also can display visual cues to activate the motions against freezing. With the safe construction design and the interactive training application, the robot can be used in home treatment. The functional performance of robot are verified. The experimental results show that the robot is able to correctly provide cues and feedback with respect to gait events and help against festination and freezing of gait.

关键词： Training Legged locomotion Visualization Force Resists Rendering (computer graphics) Real-time systems

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