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Accuracy analysis of omnidirectional mobile manipulator with mecanum wheels

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Advances in Manufacturing 2016年第4期4卷 363-370页

作者： Shuai Guo Yi Jin Sheng Bao feng-feng xi Shanghai Key Laboratory of Intelligent Manufacturing andRobotics Shanghai University Shanghai People's Republicof China Department of Aerospace Engineering Ryerson UniversityToronto Canada

This article is based on the omnidirectional mobile manipulator with mecanum wheels built at Shanghai University. The article aims to find and analyze the parameters of kinematic equation of the omnidirectional system which affects its motion accuracy. The method of solving the parameter errors involves three phases. The first step is equation operation to achieve the equation of relative errors. The second step is to obtain the displacement errors of the system via experiment and combine the error results with kinematic equation deduction to solve the geometric parameter errors in two methods. The third step is to verify its validity via comparing experiments. We can then revise its kinematics equation afterwards.

关键词： Mecanum wheel Displacement error MonteCarlo analysis Interval analysis

Framework on robotic percussive riveting for aircraft assembly automation

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Advances in Manufacturing 2013年第2期1卷 112-122页

作者： feng-feng xi Lin Yu xiao-Wei Tu Robotic and Automation Center Shanghai University Department of Aerospace Engineering Ryerson University Department of Automation and Instruments Shanghai University

Presented in this paper is a framework for the implementation of a robotic percussive riveting system, a new robot application for aircraft assembly. It is shown here that a successful robot application to the automation of a process requires in-depth research of the process and the interaction with the robot. For this purpose, a process plan- ning-driven approach is proposed to guide a robot applica- tion research. A typical process planning will involve a list of key considerations including： process sequence, process parameters, process tooling, and process control. Through this list, a number of key research issues are identified for robotic percussive riveting, such as rivet pattern planning, rivet time determination, rivet tooling design and rivet insertion control. The detailed research on these issues has effectively created know-how for the successful implemen- tation of our robotic percussive riveting system.

关键词： Aircraft assembly Assembly automation Robotic riveting Percussive riveting Process planning

Robust identification of weld seam based on region of interest operation

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Advances in Manufacturing 2020年第4期8卷 473-485页

作者： Ying-Zhong Tian Hong-Fei Liu Long Li Wen-Bin Wang Jie-Cai feng feng-feng xi Guang-Jie Yuan School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200444People's Republic of China School of Mechanical and Electrical Shenzhen PolytechnicShenzhen 518055GuangdongPeople's Republic of China Shanghai Rui Rong Laser Welding Technology Co. LtdShanghai 201306People's Republic of China Department of Mechanical Aerospace and Industrial EngineeringRyerson UniversityTorontoCanada

For welding path determination,the use of vision sensors is more effctive compared with complex ofline programming and teaching in small to medium volume production.However,interference factors such as scratches and stains on the surface of the workpiece may affect the extraction of weld information.In the obtained weld image,the weld seams have two distinct features related to the workpiece,which are continuous in a single process and separated from the workpiece's gray value.In this paper,a novel method is proposed to identify the welding path based on the region of interest(ROI)opera-tion,which is concentrated around the weld seam to reduce the interference of external noise.To complete the identi-fication of the entire welding path,a novel algorithm is used to adaptively generate a dynamic ROI(DROI)and perform iterative operations.The identification accuracy of this algorithm is improved by setting the boundary condi-tions within the ROI.Moreover,the experimental results confirm that the coefficient factor used for determining the ROI size is a pivotal influencing factor for the robustness of the algorithm and for obtaining an optimal solution.With this algorithm,the welding path identification accuracy is within 2 pixels for three common butt weld types.

关键词： Passive vision Noise reduction Welding path identification Region of interest(ROI)

Modeling and simulation of percussive impact for robotic riveting system

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Advances in Manufacturing 2014年第4期2卷 344-352页

作者： Shuai Guo Song-Liang Nie feng-feng xi Tao Song Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Department of Aerospace Engineering Ryerson University

Riveting is one of the major joining methods used in assembly, and the robotic riveting has been grad- ually introduced into aircraft industry. In this paper, a method is presented for modeling and simulation of per- cussive robotic riveting. In percussive riveting, vibration always exists. When an impact force is employed, a forced vibration will be induced. If it resonates with a robot nat- ural frequency, the vibration will cause damage to the robot. The main content of this paper is divided into three parts. Firstly, a robot dynamic model is established to compute the driving torque for each joint. Secondly, vibration responses under impact are analyzed for the percussive riveting process. Thirdly, the effect of riveting on robot vibration is studied over the robot workspace. The purpose of this paper is to discuss the suitable regions for riveting where the robot vibration is very minimal. It is shown that based on the presented method an appropriate trajectory can be planned for robotic riveting.

关键词： Robotic dynamics Analysis Vibrationresponse Impact force Riveting

Tracking and localization for omni-directional mobile industrial robot using reflectors

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Advances in Manufacturing 2018年第1期6卷 118-125页

作者： Shuai Guo Ting-Ting Fang Tao Song feng-feng xi Bang-Guo Wei Shanghai Key Laboratory of Intelligent Manufacturing andRobotics Shanghai University Shanghai 200444 People'sRepublic of China Department of Aerospace Engineering Ryerson UniversityToronto Canada

In this paper, an improved tracking and local-ization algorithm of an omni-directional mobile industrialrobot is proposed to meet the high positional accuracyrequirement, improve the robot＇s repeatability positioningprecision in the traditional trilateral algorithm, and solvethe problem of pose lost in the moving process. Lasersensors are used to identify the reflectors, and by associ-ating the reflectors identified at a particular time with thereflectors at a previous time, an optimal triangular posi-tioning method is applied to realize the positioning andtracking of the robot. The experimental results show thatpositioning accuracy can be satisfied, and the repeatabilityand anti-jamming ability of the omni-directional mobileindustrial robot will be greatly improved via this algorithm.

关键词： Mobile industrial robot Tracking and positioning Matching

Contributors to tidal duration asymmetry with varied coastline configurations on western shelf of Yellow Sea

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Water Science and Engineering 2024年第1期17卷 1-12页

作者： xi feng Zheng Li Hui feng Jia-yan Yang Shou-peng xie Wei-bing Fenag College of Harbor Coastal and Offshore Engineering Hohai UniversityNanjing 210098China China Harbour Engineering Co. LidBeijing 100027China Key Laboratory of Port Waterway and Sedimentation Engineering of the Ministry of CommunicationsNanjing 210029China China South-to-North Water Diversion Corporation Limited Beijing 100036China

Coastal management in China is confronted with an urgent choice between natural restoration and maintenance of existing seawalls and reclaimed land for economic development.A key criterion for making this decision is the resilience to coastal flooding,which depends on the ability to predict tidal level.Tidal duration asymmetry(TDA)is a key parameter in determination of the arrival and duration of flood tides.This study selected the western inner shelf of the Yellow Sea(WYS)as the study area and investigated the responses of TDA to different shoreline configurations and relative sea level rise.The responses of TDA to shoreline reconstruction yielded spatial variability locally and remotely.In the nearshore area,the responses of TDA to the complex ocean environment mainly originated from the combined functions of reflection,bottom friction,and advection,which controlled the energy transfer from M2 or S2 constituents to their overtides or compound tides.The sensitivity of TDA to coastline typologies was not limited to coastal waters but could stretch over the entire inner shelf.The vulnerability of tidal responses was due to the displacement of the M2 amphidrome of the Kelvin wave on the WYS,which in turn changed tidal energy fluxes over the regime.The relative sea level rise could intensify the feedback of TDA to seawalls and land reclamation.

关键词： Tidal duration asymmetry Western inner shelf of Yellow Sea Natural restoration Relative sea level rise Tidal amphidrome

Applying Machine Learning Approach to Explore Childhood Circumstances and Self-Rated Health in Old Age-China and the US,2020-2021

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China CDC weekly 2024年第11期6卷 213-218,I0008-I0013页

作者： Shutong Huo Derek feng Thomas M.Gill xi Chen Department of Health Society&BehaviorPublic HealthUniversity of CaliforniaIrvineCAUSA Department of Statistics and Data Science Yale UniversityNew HavenCTUS Department of Internal Medicine Yale School of MedicineNew HavenCTUS Department of Health Policy and Management Yale School of Public HealthNew HavenCTUS Department of Economics Yale UniversityNew HavenCTUS.

Introduction:Childhood circumstances impact senior health,prompting the introduction of machine learning methods to assess their individual and collective contributions to senior health.Methods:Using health and retirement study(HRS)and China Health and Retirement Longitudinal Study(CHARLS),we analyzed 2,434 American and 5,612 Chinese participants aged 60 and above.Conditional inference trees and forests were employed to estimate the influence of childhood circumstances on self-rated health(SRH).Results:The conventional method estimated higher inequality of opportunity(IOP)values in both China(0.039,accounting for 22.67%of the total Gini coefficient 0.172)and the US(0.067,accounting for 35.08%of the total Gini coefficient 0.191).In contrast,the conditional inference tree yielded lower estimates(China:0.022,accounting for 12.79%of 0.172;US:0.044,accounting for 23.04%of 0.191),as did the forest(China:0.035,accounting for 20.35%of 0.172;US:0.054,accounting for 28.27%of 0.191).Childhood health,financial status,and regional differences were key determinants of senior health.The conditional inference forest consistently outperformed others in predictive accuracy,as demonstrated by lower out-of-sample mean squared error(MSE).Discussion:The findings emphasize the need for early-life interventions to promote health equity in aging populations.Machine learning showcases the potential in identifying contributing factors.

关键词： collective inequality estimates

CToMP: a cycle-task-oriented memory protection scheme for unmanned systems

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Science China(Information Sciences) 2024年第6期67卷 399-417页

作者： Chengyan MA Ning xi Di LU Yebo feng Jianfeng MA School of Cyber Engineering Xidian University School of Computer Science and Technology Xidian University Department of Computer and Information Science University of Oregon

Memory corruption attacks(MCAs) refer to malicious behaviors of system intruders that modify the contents of a memory location to disrupt the normal operation of computing systems, causing leakage of sensitive data or perturbations to ongoing processes. Unlike general-purpose systems, unmanned systems cannot deploy complete security protection schemes, due to their limitations in size, cost and performance.MCAs in unmanned systems are particularly difficult to defend against. Furthermore, MCAs have diverse and unpredictable attack interfaces in unmanned systems, severely impacting digital and physical sectors. In this paper, we first generalize, model and taxonomize MCAs found in unmanned systems currently, laying the foundation for designing a portable and general defense approach. According to different attack mechanisms,we found that MCAs are mainly categorized into two types — return2libc and return2shellcode. To tackle return2libc attacks, we model the erratic operation of unmanned systems with cycles and then propose a cycle-task-oriented memory protection(CToMP) approach to protect control flows from tampering. To defend against return2shellcode attacks, we introduce a secure process stack with a randomized memory address by leveraging the memory pool to prevent Shellcode from being executed. Moreover, we discuss the mechanism by which CTo MP resists the return-oriented programming(ROP) attack, a novel variant of return2libc attacks. Finally, we implement CTo MP on CUAV V5+ with Ardupilot and Crazyflie. The evaluation and security analysis results demonstrate that the proposed approach CTo MP is resilient to various MCAs in unmanned systems with low footprints and system overhead.

关键词： unmanned system memory corruption attack memory protection system security randomized memory address

Corporate Credit Ratings Based on Hierarchical Heterogeneous Graph Neural Networks

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Machine Intelligence Research 2024年第2期21卷 257-271页

作者： Bo-Jing feng xi Cheng Hao-Nan Xu Wen-Fang Xue Center for Research on Intelligent Perception and Computing National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China

order to help investors understand the credit status of target corporations and reduce investment risks,the corporate credit rating model has become an important evaluation tool in the financial market.These models are based on statistical learning,machine learning and deep learning especially graph neural networks(GNNs).However,we found that only few models take the hierarchy,heterogeneity or unlabeled data into account in the actual corporate credit rating process.Therefore,we propose a novel framework named hierarchical heterogeneous graph neural networks(HHGNN),which can fully model the hierarchy of corporate features and the heterogeneity of relationships between corporations.In addition,we design an adversarial learning block to make full use of the rich unlabeled samples in the financial data.Extensive experiments conducted on the public-listed corporate rating dataset prove that HHGNN achieves SOTA compared to the baseline methods.

关键词： Corporate credit rating hierarchical relation heterogeneous graph neural networks adversarial learning