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2021 International Conference on robotics and Control engineering, RobCE 2021

作者： Che, Junjie Pan, Yang Yan, Wei Yu, Jiexian Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen518055 China Guangdong Prov. Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9781450389471

Bio-inspired biped robots require high level dynamic control when walking or jumping. Compared with 4 or 6 legged robots, mechanisms of biped robots are more complicated and have more DOFs, which means both kinematical and dynamic models are more complex. In this paper, we formulated the kinematic models of ostrich bionic biped robot, which apply serial-parallel hybrid mechanism with 13 joints (5 active, 8 passive) each leg. The mechanism topology patterns are analyzed during walking, jumping and standing. We defined the feet as 5-DOFs end-effectors and both forward and inverse kinematic models are formulated using screw theory. An ordinary walking gait based on inverted pendulum was used to test the models and the results show that the robot can walk very well in simulation environments. The research of this paper has obvious application significance for the design, iteration and control of ostrich bionic biped robot. © 2021 ACM.

关键词： Bionics

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A kinematic calibration method for robots based on the PGTF error model and Levenberg-Marquardt algorithm

A kinematic calibration method for robots based on the PGTF ...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Zhi Zheng Jin Wang Jun Zhu Luan Liu Haiyun Zhang Guodong Lu State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou China Robotics Research Center of Yuyao City Ningbo China Robotics Institute of Zhejiang University Hangzhou China School of Robotics Ningbo University of Technology Ningbo China Zhejiang Qiantang Robot and Intelligent Equipment Research Co. LTD Hangzhou China

Robots use motors for power output and realize joint motion through reducers and mechanical transmissions, which affect the absolute positioning accuracy. In view of this problem, an error model based on Preprocessing-Geometric-Transmission-Flexibility (PGTF) is proposed and solved by Levenberg-Marquardt algorithm. First, the theoretical kinematic model is established by MD-H model method. Second, the data was pre-processed in dimension upgrade and the robot error identification model was established for geometric error, transmission error and flexible error. Third, Levenberg-Marquardt algorithm was used to find the global convergence solution to realize the identification of error parameters, and the actual robot kinematic model was compensated. Finally, the experiment is carried out on the real robot machine. Through theoretical analysis and verification of real machine data, the average error of kenbei-5kg robot is reduced from 6.8787 mm to 0.1267 mm, the positioning accuracy is improved by 98.16%, the accuracy compensation algorithm is accurate, and the compensation effect is remarkable.

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Unprecedented Smart Algorithm for Uninterrupted SDN Services During DDoS Attack

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Computers, Materials & Continua 2022年第1期70卷 875-894页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Rizaludin Kaspin Iram Haider Sana Nisar J.P.C.Rodrigues Bhawani Shankar Chowdhry Muhammad AslamUqaili Satya Prasad Majumder Danda B.Rawat Richard Etengu Rajkumar Buyya Faculty of Computing&Informatics Multimedia UniversityPersiaranMultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation Centre63000CyberjayaSelangorMalaysia Federal University of Piauí(UFPI) TeresinaPIBrazil Instituto de Telecomunica珲es 6201-001Covilh?Portugal National Center of Robotics and Automation-Condition Monitoring Systems Lab MUETJamshoroPakistan Department of Electrical and Electronic Engineering BUETDhaka1205Bangladesh Department of Electrical Engineering and Computer Science Data Science and Cybersecurity CenterHoward UniversityWashingtonDCUSA Cloud Computing and Distributed Systems(CLOUDS)Laboratory School of Computing and Information SystemsThe University of MelbourneMelbourneVIC 3053Australia

In the design and planning of next-generation Internet of Things(IoT),telecommunication,and satellite communication systems,controller placement is crucial in software-defined networking(SDN).The programmability of the SDN controller is sophisticated for the centralized control system of the entire ***,it creates a significant loophole for the manifestation of a distributed denial of service(DDoS)attack ***,recently a Distributed Reflected Denial of Service(DRDoS)attack,an unusual DDoS attack,has been ***,minimal deliberation has given to this forthcoming single point of SDN infrastructure failure ***,recently the high frequencies of DDoS attacks have increased *** this paper,a smart algorithm for planning SDN smart backup controllers under DDoS attack scenarios has *** proposed smart algorithm can recommend single or multiple smart backup controllers in the event of DDoS *** obtained simulated results demonstrate that the validation of the proposed algorithm and the performance analysis achieved 99.99%accuracy in placing the smart backup controller under DDoS attacks within 0.125 to 46508.7 s in SDN.

关键词： SDN smart algorithm RTZLK-DAASCP DDoS attack DRDoS

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Posture Estimation and Trajectory Tracking for SQuRo: a Small-sized Quadruped Robotic Rat

Posture Estimation and Trajectory Tracking for SQuRo: a Smal...

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IEEE International Conference on Cyborg and Bionic systems (CBS)

作者： Junhui Gao Rongjie Du Xiaolong Quan Guanglu Jia Qiang Huang Toshio Fukuda Qing Shi School of Mechatronical Engineering Intelligent Robotics InstituteBeijing Institute of Technology Beijing China Ministry of Education >Laboratory of Biomimetic Robots and Systems(Beijing Institute of Technology) Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Ministry of Education Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Beijing China

Large quadruped robots have shown high environmental adaptability and promising applications. However, due to the difficulty of integrating multiple sensors or highperformance CPU in such a limited dimension, which strongly hindered the perception and calculation ability, quadruped robots in small scale haven’t shown equally performance. To overcome this limitation, we integrated the inertial measurement unit (IMU) into the small-sized robotic rat SQuRo, and proposed simplified control strategies to enhance its robustness. The improvements includes three parts: 1) A posture control strategy is proposed and verified by posture adjustment in a slope test; 2) Straight line tracking was achieved by detecting and controlling the yaw angle of SQuRo; 3) The autonomous fall recovery was achieved by detecting the fall and executed a predefined fall recovery strategy.

关键词： Measurement units Trajectory tracking Kinematics Inertial navigation Rats Robot sensing systems Robustness

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Correction of measurement accuracy for optical measuring machines depending on the direction vector of the point

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Measurement: Sensors 2025年 38卷

作者： Harmatys, Wiktor Gąska, Adam Gąska, Piotr Gruza, Maciej Laboratory of Coordinate Metrology Cracow University of Technology al. Jana Pawla II 37 Cracow31-864 Poland Department of Manufacturing Systems Faculty of Mechanical Engineering and Robotics AGH University of Krakow al. Mickiewicza 30 Krakow30-059 Poland

Optical measurement techniques are one of the most frequently used coordinate measurement systems in factory conditions. Due to their continuous development and miniaturization, this allowed them to be installed in various types of coordinate measuring machines, as a result of which, the machine equipped with a classic contact head and an optical head enables multi-sensor measurement. The growing popularity of optical heads is due to the fact that they enable non-contact measurement of even small and sensitive objects, which in many cases is impossible to do with a contact head. In addition, they owe their popularity to the fact that a significantly smaller number of precise mechanical and electronic elements are used in their construction. Another advantage is that they enable collecting a large number of points in a short time, which is more difficult with traditional contact systems, and with the development of these techniques, optical heads offer increasingly higher accuracy. However, the disadvantage of this method is that the stability and accuracy of measurements using this method depend on a large number of factors, including: lighting conditions, quality of measured surface and its reflectivity. Another problem that has not been fully solved is the lack of direct correlation between contact and non-contact measurements due to the fact that it is very difficult to obtain a measurement of exactly the same point using these two measurement techniques. Another problem related to the measurement accuracy of this type of measuring heads, especially for the end user, is that the metrological software of most manufacturers is closed software, i.e. no one other than the manufacturer has access to the source code and therefore the techniques and algorithms for detecting a point in the image are known only to the manufacturer. Due to the fact that different algorithms may detect a point in the image in a different way, especially if the direction vector is not fully

关键词： Coordinate measuring machines

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Scarefusion:Side Channel Analysis Data Restoration with Diffusion Model

SSRN

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SSRN 2024年

作者： Lu, Zeng Longde, Yan Fei, Wan Ning, Yang Xiang, Li Aidong, Chen Jiancheng, Zhang YanLong, Zhang Shuo, Wang Jing, Zhou Beijing Key Laboratory of Information Service Engineering Beijing Union University Beijing100101 China College of Robotics Beijing Union University Beijing100101 China Research Centre for Multi-Intelligent Systems Beijing100101 China Beijing Union University China

Side-channel analysis based on deep learning is sensitive to data quality. We propose SCARefusion, a latent diffusion model using U-Net, to address data imbalance in power consumption traces. SCARefusion retains high-resolution information through Conditional Nonlinear Activation Free Blocks (CNAFBlocks), downsampling, and upsampling modules. This model generates balanced class data, mitigating dataset imbalance and avoiding GAN instability. Using Correlation Power Analysis (CPA), we compare correlation coefficients between hypothetical and measured traces. The generated traces' effectiveness is validated using CNN attacks. Experimental results on the ASCADf dataset show that SCARefusion generates traces consistent with original leakage points and successfully extracts the correct key. We also discuss strategies to reduce learning rate and optimize network architecture to address loss oscillation, enhancing the performance and robustness of deep learning in side-channel analysis. © 2024, The Authors. All rights reserved.

关键词： Network architecture

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A Robust Visual SLAM System for Small-Scale Quadruped Robots in Dynamic Environments

A Robust Visual SLAM System for Small-Scale Quadruped Robots...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Chengyang Li Yulai Zhang Zhiqiang Yu Xinming Liu Qing Shi Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing School of Medical Technology Beijing Institute of Technology Jiaxing China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing China Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This paper presents a robust visual SLAM system designed for small-scale quadruped robots (ViQu-SLAM) for accurate localization, especially to mitigate the issue of erroneous data association caused by moving objects in dynamic environments. The proposed approach leverages a selfadaptive framework that integrates semantic segmentation with alterations in the spatial location of categorized map points. Besides, combination of leg odometry derived from forward kinematics with IMU provides scale information for positional transformations between keyframes, thus optimizing the overall localization accuracy of quadruped robots. At last, we performed evaluation across various stages and the results demonstrate competitive performance, with 53.16% reduction in average absolute trajectory error compared to that of ORB-SLAM3 in dynamic benchmark datasets. As a result, ViQu-SLAM, including visual and IMU-fused leg odometry, exhibits promising results on a small quadruped robot, reducing positioning errors in dynamic scenes by an average of 29.36% compared to existing state-of-the-art methods.

关键词： Legged locomotion Location awareness Visualization Simultaneous localization and mapping Accuracy Semantic segmentation Heuristic algorithms Object detection Quadrupedal robots Odometry

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Optimization of Simulation Parameters of Input Shaper Based on Genetic Algorithm 2

Optimization of Simulation Parameters of Input Shaper Based ...

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2nd IEEE International Conference on Advanced Technologies in Intelligent Control, Environment, Computing and Communication engineering, ICATIECE 2022

作者： Yi, Tao Pei, Quanshen Li, Deying Wei, Shugong Jia, Danping Zhang, Hualiang Hunan University of Information Changsha China School of Information Science and Engineering Shenyang University of Technology Shenyang China College of Physics and Electronic Engineering Guangxi Normal University for Nationalities Chongzuo China Chinese Academy of Sciences Shenyang Institute of Automation Key Laboratory of Networked Control Systems Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China

ISBN: (纸本)9781665493963

In the motion control system, input shaper is often used to suppress the residual oscillation of high-precision positioning system, but the selection of input shaper parameters is difficult. In view of the difficulty of selecting input shaper parameters, this paper proposes to use genetic algorithm to select the parameters of input shaper. Firstly, the input shaper is designed in the light of the three-loop mathematical model of motor;Secondly, because the genetic algorithm directly optimizes the output of the motor and the algorithm can reduce the influence of the deviation of generator parameters on the parameter selection of the input shaper to a certain extent, the parameters of the input shaper are selected by the genetic algorithm to optimize the output of the motor;In the finish, a comparative experiment between a system with input shaper and a system with simple PID control is carried out. The results show that the optimized system can obtain higher robustness and smaller tracking deviation. © 2022 IEEE.

关键词： Genetic algorithms

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Compensating for the Effect of Absence of Joint Movements in EMG-based Continuous Movement Decoding with a Deep Learning Approach

Compensating for the Effect of Absence of Joint Movements in...

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

作者： Lizhi Pan Zhongyi Ding Chengjun Li Haifeng Zhao Ruinan Mu Jianmin Li Jinhua Li Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education School of Mechanical Engineering Tianjin University Tianjin China Institute of Medical Robotics and Intelligent Systems Tianjin University Tianjin China Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350391916

ISBN: (纸本)9798350391923

In recent decades, human-machine interfaces (HMIs) based on electromyography (EMG) signals have become research hotspots in the fields of rehabilitation engineering, aerospace, and human factors engineering. However, the absence of joint movements can influence the performance of HMIs in the continuous movement decoding. Therefore, it has become an urgent problem to improve the quality of EMG signals with the absence of joint movements. In this study, a deep learning (DL) method is proposed based on the convolutional neural network (CNN) to compensate for the absence of joint movements in EMG-based continuous movement decoding. Ten able-bodied subjects were recruited to complete a series of movements with the metacarpophalangeal (MCP) and wrist joints unconstrained (MWJU) and constrained (MWJC). Half of the EMG signals for the constrained joint movements were compensated with the proposed CNN-based method (CNN-EMG), which were then compared with the other half of the constrained EMG signals (MWJC-EMG) and the signals without joint constraints (MWJU-EMG). The Pearson’s correlation coefficient (r) and the normalized root mean square error (NRMSE) were employed as the indexes to quantify the performance of continuous movement decoding with three groups of EMG signals. Compared with the performance of MWJC-EMG, the average r values for wrist and MCP flexion/extension of CNN-EMG signals increased from 0.8 to 0.84 and from 0.49 to 0.66, respectively. Compared with the performance of MWJC-EMG signals, the average NRMSE values for wrist and MCP flexion/extension of CNN-EMG signals decreased from 0.21 to 0.19 and 0.31 to 0.26, respectively. The analysis results demonstrated that the proposed DL method can significantly improve the continuous movement decoding performance of HMIs through compensating the effect of absence of joint movements.

关键词： Wrist Deep learning Musculoskeletal system Mechatronics Machine vision Electromyography Decoding Convolutional neural networks Indexes Root mean square

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A fireworks algorithm based path planning method for amphibious robot

A fireworks algorithm based path planning method for amphibi...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Qi, Yuanyang Liu, Jincun Yu, Junzhi College of Engineering Peking University State Key Laboratory for Turbulence and Complex Systems BIC-ESAT Department of Advanced Manufacturing and Robotics Beijing100871 China College of Information and Electrical Engineering China Agricultural University Beijing100083 China

ISBN: (纸本)9781665436786

This paper proposes a fireworks algorithm based path planning method for amphibious robots that operate in terraqueous environments. Firstly, the amphibious path planning is formulated into a constrained optimization problem by coordinate transformation and line segmentation. Distance, energy consumption, and robot mode switching costs regarding the unconventional characteristics of the amphibious environment are considered. Secondly, the fireworks algorithm (FWA) and the bare bones fireworks algorithm (BBFWA) are briefly introduced. Finally, both methods have been implemented for solving the amphibious path planning problem. Simulation experiments have been conducted to explore the effectiveness and performance of both methods. Results indicate that our proposed path planning method for terraqueous environments is effective, and the fireworks algorithm outperforms the bare bones fireworks algorithm despite the latter surpasses several enhanced variants of the former on certain benchmarks. © 2021 IEEE.

关键词： Motion planning

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