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Joint moment estimation for hip exoskeleton control: A generalized moment feature generation method

Biomimetic Intelligence and robotics 2025年

作者： Yuanwen Zhang Jingfeng Xiong Haolan Xian Chuheng Chen Xinxing Chen Haipeng Liang Chenglong Fu Yuquan Leng State Key Laboratory of Robotics and Systems School of Biomedical Engineering Harbin Institute of Technology Shenzhen 518055 China Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen 518055 China School of Engineering and Materials Science Queen Mary University of London London E1 4NS UK

Hip joint moments during walking are the key foundation for hip exoskeleton assistance control. Most recent studies have shown estimating hip joint moments instantaneously offers a lot of advantages compared to generating assistive torque profiles based on gait estimation, such as simple sensor requirements and adaptability to variable walking speeds. However, existing joint moment estimation methods still suffer from a lack of personalization, leading to estimation accuracy degradation for new users. To address the challenges, this paper proposes a hip joint moment estimation method based on generalized moment features (GMF). A GMF generator is constructed to learn GMF of the joint moment which is invariant to individual variations while remaining decodable into joint moments through a dedicated decoder. Utilizing this well-featured representation, a GRU-based neural network is used to predict GMF with joint kinematics data, which can easily be acquired by hip exoskeleton encoders. The proposed estimation method achieves a root mean square error of 0.1180 ± 0.0021 Nm/kg under 28 walking speed conditions on a treadmill dataset, improved by 6.5% compared to the model without body parameter fusion, and by 8.3% for the conventional fusion model with body parameter. Furthermore, the proposed method was employed on a hip exoskeleton with only encoder sensors and achieved an average 20.5% metabolic reduction ( p < 0 . 01 ) for users compared to assist-off condition in level-ground walking.

关键词： Lower-limb exoskeleton Hip joint moment estimation Deep learning

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PEBO-SLAM: Observer Design for Visual Inertial SLAM with Convergence Guarantees

arXiv

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arXiv 2023年

作者： Yi, Bowen Jin, Chi Wang, Lei Shi, Guodong Ila, Viorela Manchester, Ian R. The Australian Centre for Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney SydneyNSW2006 Australia The TuSimple Inc. Liangmaqiao Road Beijing China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China

This paper introduces a new linear parameterization to the problem of visual inertial simultaneous localization and mapping (VI-SLAM)—without any approximation—for the case only using information from a single monocular camera and an inertial measurement unit. In this problem set, the system state evolves on the nonlinear manifold SE(3)×3n, on which we design dynamic extensions carefully to generate invariant foliations, such that the problem can be reformulated into online constant parameter identification, then interestingly with linear regression models obtained. It demonstrates that VI-SLAM can be translated into a linear least squares problem, in the deterministic sense, globally and exactly. Based on this observation, we propose a novel SLAM observer, following the recently established parameter estimation-based observer (PEBO) methodology. A notable merit is that the proposed observer enjoys almost global asymptotic stability, requiring neither persistency of excitation nor uniform complete observability, which, however, are widely adopted in most existing works with provable stability but can hardly be assured in many practical scenarios. © 2023, CC BY.

关键词： Parameter estimation

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Tension Analysis of Small Motor Stator Winding Tensioning Process

Tension Analysis of Small Motor Stator Winding Tensioning Pr...

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作者： Zhao, Yanling Zhang, Zhao Xiang, Jingzhong Bao, Yudong State Key Laboratory of Robotics and Systems Harbin150080 China School of Mechanical and Power Engineering Harbin University of Science and Technology Harbin150080 China

In view of the small motor stator winding due to the size of the tension on the enameled wire is different, so that the winding tightness is different and lead to enameled wire damage or motor can not be used normally. Through the establishment of the tension model of the tensioning process, the stress of each layer of enameled wire during tensioning is analyzed, which involves the mechanical theory of tensioning process and the theory of thick-walled thin cylinder. According to this theory, the mechanical behavior of the enameled wire during the tensioning process is studied, the influence of tension on the radial stress and hoop stress of the special point and the variation law are obtained. After simulation and experiment, the results show that the tension and the number of winding layers have different effects on the radial and hoop stress of the special points. Applying reasonable tension can effectively ensure the normal operation of the motor and greatly increase its reliability. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Winding

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Joint Counting, Detection and Re-Identification for Multi-Object Tracking

arXiv

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arXiv 2022年

作者： Ren, Weihong Wu, Denglu Cao, Hui Chen, Xi'ai Han, Zhi Liu, Honghai The School of Mechanical Engineering and Automation State Key Lab of Robotics and Systems Harbin Institute of Technology Shenzhen518055 China The Shenzhen Duorou Intelligent System Co. Ltd. Shenzhen518055 China The School of Electrical Engineering Xi’an Jiaotong University Xi’an710049 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science Beijing110169 China

The recent trend in 2D multiple object tracking (MOT) is jointly solving detection and tracking, where object detection and appearance feature (or motion) are learned simultaneously. Despite competitive performance, in crowded scenes, joint detection and tracking usually fail to find accurate object associations due to missed or false detections. In this paper, we jointly model counting, detection and re-identification in an end-to-end framework, named CountingMOT, tailored for crowded scenes. By imposing mutual object-count constraints between detection and counting, the CountingMOT tries to find a balance between object detection and crowd density map estimation, which can help it to recover missed detections or reject false detections. Our approach is an attempt to bridge the gap of object detection, counting, and re-Identification. This is in contrast to prior MOT methods that either ignore the crowd density and thus are prone to failure in crowded scenes, or depend on local correlations to build a graphical relationship for matching targets. The proposed MOT tracker can perform online and real-time tracking, and achieves the state-of-the-art results on public benchmarks MOT16 (MOTA of 79.7%), MOT17 (MOTA of 81.3%) and MOT20 (MOTA of 78.9%). Source code is available at https://***/weihong9/CountingMOT. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

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Towards Accurate Unified Anomaly Segmentation

Towards Accurate Unified Anomaly Segmentation

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IEEE Workshop on Applications of Computer Vision (WACV)

作者： Wenxin Ma Qingsong Yao Xiang Zhang Zhelong Huang Zihang Jiang S. Kevin Zhou Division of Life Sciences and Medicine School of Biomedical Engineering University of Science and Technology of China (USTC) Hefei Anhui China Center for Medical Imaging Robotics Analytic Computing & Learning (MIRACLE) USTC Suzhou Institute for Advance Research Suzhou Jiangsu China Stanford University Palo Alto California United State School of Medicine Shanghai University Shanghai China Key Laboratory of Precision and Intelligent Chemistry USTC Hefei Anhui China Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

Unsupervised anomaly detection (UAD) from images strives to model normal data distributions, creating discriminative representations to distinguish and precisely localize anomalies. Despite recent advancements in the efficient and unified one-for-all scheme, challenges persist in accurately segmenting anomalies for further monitoring. Moreover, this problem is obscured by the widely-used AUROC metric under imbalanced UAD settings. This motivates us to emphasize the significance of precise segmentation of anomaly pixels using pAP and DSC as metrics. To address the unsolved segmentation task, we introduce the Unified Anomaly Segmentation (UniAS). UniAS presents a multi-level hybrid pipeline that progressively enhances normal information from coarse to fine, incorporating a novel multi-granularity gated CNN (MGG-CNN) into Transformer layers to explicitly aggregate local details from different granularities. UniAS achieves state-of-the-art anomaly segmentation performance, attaining 65.12/59.33 and 40.06/32.50 in pAP/DSC on the MVTec-AD and VisA datasets, respectively, surpassing previous methods significantly. The codes are shared at https://***/Mwxinnn/UniAS.

关键词： Measurement Image segmentation Computer vision Codes Pipelines Logic gates Transformers Data models Monitoring Anomaly detection

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Modeling Spoof Noise by De-spoofing Diffusion and its Application in Face Anti-spoofing

arXiv

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arXiv 2024年

作者： Zhang, Bin Zhu, Xiangyu Zhang, Xiaoyu Lei, Zhen Institute of Information Engineering Chinese Academy of Sciences China School of Cyber Security University of Chinese Academy of Sciences China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation Chinese Academy of Sciences China

Face anti-spoofing is crucial for ensuring the security and reliability of face recognition systems. Several existing face anti-spoofing methods utilize GAN-like networks to detect presentation attacks by estimating the noise pattern of a spoof image and recovering the corresponding genuine image. But GAN’s limited face appearance space results in the denoised faces cannot cover the full data distribution of genuine faces, thereby undermining the generalization performance of such methods. In this work, we present a pioneering attempt to employ diffusion models to denoise a spoof image and restore the genuine image. The difference between these two images is considered as the spoof noise, which can serve as a discriminative cue for face anti-spoofing. We evaluate our proposed method on several intra-testing and inter-testing protocols, where the experimental results showcase the effectiveness of our method in achieving competitive performance in terms of both accuracy and generalization. Copyright © 2024, The Authors. All rights reserved.

关键词： Face recognition

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Biomarkers of aging

引用

Science China(Life Sciences) 2023年第5期66卷 893-1066页

作者： Aging Biomarker Consortium Hainan Bao Jiani Cao Mengting Chen Min Chen Wei Chen Xiao Chen Yanhao Chen Yu Chen Yutian Chen Zhiyang Chen Jagadish K Chhetri Yingjie Ding Junlin Feng Jun Guo Mengmeng Guo Chuting He Yujuan Jia Haiping Jiang Ying Jing Dingfeng Li Jiaming Li Jingyi Li Qinhao Liang Rui Liang Feng Liu Xiaoqian Liu Zuojun Liu Oscar Junhong Luo Jianwei Lv Jingyi Ma Kehang Mao Jiawei Nie Xinhua Qiao Xinpei Sun Xiaoqiang Tang Jianfang Wang Qiaoran Wang Siyuan Wang Xuan Wang Yaning Wang Yuhan Wang Rimo Wu Kai Xia Fu-Hui Xiao Lingyan Xu Yingying Xu Haoteng Yan Liang Yang Ruici Yang Yuanxin Yang Yilin Ying Le Zhang Weiwei Zhang Wenwan Zhang Xing Zhang Zhuo Zhang Min Zhou Rui Zhou Qingchen Zhu Zhengmao Zhu Feng Cao Zhongwei Cao Piu Chan Chang Chen Guobing Chen Hou-Zao Chen Jun Chen Weimin Ci Bi-Sen Ding Qiurong Ding Feng Gao Jing-Dong JHan Kai Huang Zhenyu Ju Qing-Peng Kong Ji Li Jian Li Xin Li Baohua Liu Feng Liu Lin Liu Qiang Liu Qiang Liu Xingguo Liu Yong Liu Xianghang Luo Shuai Ma Xinran Ma Zhiyong Mao Jing Nie Yaojin Peng Jing Qu Jie Ren Ruibao Ren Moshi Song Zhou Songyang Yi Eve Sun Yu Sun Mei Tian Shusen Wang Si Wang Xia Wang Xiaoning Wang Yan-Jiang Wang Yunfang Wang Catherine CL Wong Andy Peng Xiang Yichuan Xiao Zhengwei Xie Daichao Xu Jing Ye Rui Yue Cuntai Zhang Hongbo Zhang Liang Zhang Weiqi Zhang Yong Zhang Yun-Wu Zhang Zhuohua Zhang Tongbiao Zhao Yuzheng Zhao Dahai Zhu Weiguo Zou Gang Pei Guang-Hui Liu Aging Biomarker Consortium(ABC) Beijing 100101China CAS Key Laboratory of Genomic and Precision Medicine Beijing Institute of GenomicsChinese Academy of Sciences and China National Center for BioinformationBeijing 100101China State Key Laboratory of Stem Cell and Reproductive Biology Institute of ZoologyChinese Academy of SciencesBeijing 100101China Department of Dermatology Xiangya HospitalCentral South UniversityChangsha 410008China Hunan Key Laboratory of Aging Biology Xiangya HospitalCentral South UniversityChangsha 410008China National Clinical Research Center for Geriatric Disorders Xiangya HospitalCentral South UniversityChangsha 410008China Clinic Center of Human Gene Research Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China Hubei Clinical Research Center of Metabolic and Cardiovascular Disease Huazhong University of Science and TechnologyWuhan 430022China Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging Huazhong University of Science and TechnologyWuhan 430022China Stem Cell Translational Research Center Tongji HospitalTongji University School of MedicineShanghai 200065China Department of Nuclear Medicine Daping HospitalThird Military Medical UniversityChongqing 400042China CAS Key Laboratory of Nutrition Metabolism and Food SafetyShanghai Institute of Nutrition and HealthUniversity of Chinese Academy of SciencesChinese Academy of SciencesShanghai 200031China Shanghai Key Laboratory of Maternal Fetal Medicine Clinical and Translational Research Center of Shanghai First Maternity and Infant HospitalFrontier Science Center for Stem Cell ResearchShanghai Key Laboratory of Signaling and Disease ResearchSchool of Life Sciences and TechnologyTongji UniversityShanghai 200092China The Department of Endovascular Surgery The First Affiliated Hospital of Zhengzhou UniversityZhengzhou 450052China Key Laboratory of Regenerative Medicine of Ministry of Education Institute of Ageing and Regenerative MedicineJ

Aging biomarkers are a combination of biological parameters to(i)assess age-related changes,(ii)track the physiological aging process,and(iii)predict the transition into a pathological *** a broad spectrum of aging biomarkers has been developed,their potential uses and limitations remain poorly *** immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research:How old are we?Why do we get old?And how can we age slower?This review aims to address this ***,we summarize our current knowledge of biomarkers developed for cellular,organ,and organismal levels of aging,comprising six pillars:physiological characteristics,medical imaging,histological features,cellular alterations,molecular changes,and secretory *** fulfill all these requisites,we propose that aging biomarkers should qualify for being specific,systemic,and clinically relevant.

关键词： aging senescence biomarker clock

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Catch Planner: Catching High-Speed Targets in the Flight

arXiv

引用

arXiv 2023年

作者： Yu, Huan Wang, Pengqin Wang, Jin Ji, Jialin Zheng, Zhi Tu, Jie Lu, Guodong Meng, Jun Zhu, Meixin Shen, Shaojie Gao, Fei The State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China The Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province School of Mechanical Engineering Zhejiang University Hangzhou310027 China Robotics Institute of Zhejiang University Hangzhou310027 China Hong Kong The State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China School of Electrical Engineering Zhejiang University Hangzhou310027 China The Hong Kong University of Science and Technology Guangzhou China

Catching high-speed targets in the flight is a complex and typical highly dynamic task. However, existing methods require manual setting of catching height or time, resulting in lacks of adaptability and flexibility and cannot deal with multiple targets. To bridge this gap, we propose a planning-with-decision scheme called Catch Planner. For sequential decision making, a lightweight policy search method based on deep reinforcement learning is proposed. It is jointly trained with the motion planning and decoupled from physics to speed up training. For motion planning, we propose a trajectory optimization method that jointly optimizes the highly coupled catching time and terminal state. The core is the flexible-terminal constraint transcription. It converts the three unique constraints of catching into differentiable metrics, including equality constraints for terminal position and time, and inequality constraints that enable reasonable terminal position offset and attitude relaxation. In addition, sparse parameterization based on MINCO class considers both dynamic feasibility and collision avoidance constraints. As a result, a generally constrained quadrotor planning problem is transformed into an unconstrained optimization that can be solved reliably and efficiently. We also propose an online iterative optimization method for predicting differentiable trajectories of targets. Catch Planner provides a new paradigm for the combination of learning and planning, where all algorithms can be run in real time onboard at 100hz. Extensive experiments are carried out in real-world and simulated scenes to verify the robustness and expansibility when facing a variety of high-speed flying targets. Copyright © 2023, The Authors. All rights reserved.

关键词： Decision making

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Dual model biosensor integrated with peroxidase-like activity and self-assembly for uric acid detection

引用

Journal of materials chemistry. B 2025年 2025 May 27页

作者： Dingyitai Liang Ziqi Ding Yushu Ding Wenxuan Tang Shouzhi Yang Xiaoyu Xu Yuning Wang Kun Qian State Key Laboratory of Systems Medicine for Cancer School of Biomedical Engineering and Institute of Medical Robotics Shanghai Jiao Tong University Shanghai 200030 P. R. China. yuningwang@***.

Uric acid (UA), the final product of purine metabolism, is a crucial biomarker for gout diagnostics and highly related to various metabolic diseases. Precise detection of UA levels in serum and urine enables disease diagnosis and guides treatment. Combining the advantages of colorimetry and laser desorption/ionization mass spectrometry (LDI-MS), we developed a dual-model biosensor based on hollow CuO@Au nanocubes (h-CuO@Au NCs) for UA detection. The h-CuO@Au NCs demonstrated excellent peroxidase (POD)-like activity and were used to rapidly detect UA by colorimetric assay, with a linear range of 0.05-2 mM and limit of detection (LOD) of 35.71 μM. Moreover, the h-CuO@Au NCs achieved enrichment and detection of UA the liquid-liquid interface self-assembly-assisted LDI-MS, with a linear range of 0.01-0.5 mM, LOD of 15.6 μM, and reproducibility of <5%. In view of its advantages, the dual-model nanoplatform based on h-CuO@Au NCs achieved UA detection in serum samples by colorimetry assay and in urine samples by LDI-MS, obtaining results consistent with the commercial UA assay kit (72-511 μM for serum, = 0.956 and 2-9 mM for urine, = 0.876), presenting potential in the rapid and sensitive detection of UA in clinic.

关键词： Mass spectrometry

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A differential public PUF design for lightweight authentication 16

A differential public PUF design for lightweight authenticat...

引用

2021 International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design, SMACD 2021 and 16th Conference on PhD Research in Microelectronics and Electronics, PRIME 2021

作者： Duan, Shengyu Sai, Gaole School of Computer Engineering and Science Shanghai University Shanghai200444 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China

ISBN: (纸本)9783800755899

Physical Unclonable Functions (PUFs) have emerged as a promising primitive to provide a hardware keyless security mechanism for integrated circuit applications. Public PUFs (PPUFs) address the crucial PUF vulnerability of requiring databases to store the secrete reference information. This paper investigates one of the PPUF families, differential PPUF (dPPUF), which exploits complexly interacted logic to create time gap between actual execution and simulation, and to prevent simulation attacks. Conventional dPPUFs have high costs. We observe the repressers have large impact on simulation time, but take a great proportion in current dPPUF structure. We thereby present a represser network with specially designed interconnection and shared logic, to maintain a high circuit complexity and to reduce the area cost. We show the proposed dPPUF has similar resilience over simulation attacks as the conventional design. Area cost can be reduced by up to 44%, and thus the proposed design can be used for lightweight authentication. © VDE VERLAG GMBH.

关键词： Authentication

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