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International Conference on Computing and Networking Technology (ICCNT)

作者： Amal Mekni Jyotindra Narayan Hassène Gritli RISC Laboratory (LR16ES07) Borj Cedria Higher Institute of Information and Communication Technologies University of Carthage Tunis Tunisia Department of Mechanical Engineering Mechtronics and Robotics Laboratory Indian Institute of Technology Guwahati Guwahati Assam India Laboratory of Robotics Informatics and Complex Systems RISC Lab - LR16ES07) National Engineering School of Tunis University of Tunis El Manar Le Belvédère Tunis Tunisia

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Walking is a fundamental human activity, yet understanding its intricacies is crucial for diagnosing and treating various gait abnormalities and musculoskeletal disorders. This study investigates the machine learning-based classification of gait phases into five subphases with two training methods. Using data from 100 individuals obtained from an open-source platform. The gait cycle was divided into the following subphases: Initial Contact, Loading Response, Mid Stance, Terminal Stance, and Pre-Swing. In the first approach, a stratified random sampling method was employed, allocating 80% of data from each subphase for training and 20% for testing. The second method involved training with data from 80% participants and testing with data from 20% participants. Out of different ML algorithms, the Random Forest (RF) achieves the highest performance (99.2%) with similar results across both methods. The k-Nearest Neighbors (k-NN), the Logistic Regression (LR), the Decision Tree (DT), and the Support Vector Machine (SVM) show comparable performance ($\sim 91 \%$) with marginal improvement with the second method. Naive Bayes (NB) has a significantly lower performance ($\sim 77.7 \%$). These findings suggest that RF is a robust and effective algorithm for this task. Furthermore, the study indicates that applying machine learning techniques to datasets divided by subjects presents promising opportunities for creating precise gait analysis systems. This can assist clinicians and researchers in enhancing patient care and gaining deeper insights into human locomotion.

关键词： Training Support vector machines Radio frequency Musculoskeletal system Logistic regression Machine learning algorithms Nearest neighbor methods Sampling methods Random forests Testing

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Cooperative Motion Control Using Hybrid Acoustic-Optical Communication Networks ⁎

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IFAC-PapersOnLine 2021年第16期54卷 232-237页

作者： Rodrigo Rego Nguyen Hung Antonio Pascoal Laboratory of Robotics and Systems in Engineering and Science(LARSyS) ISR/IST University of Lisbon Lisbon Portugal

There is currently widespread interest in the development of groups of autonomous underwater vehicles for ocean exploration. This calls for the deployment of robots that can act in cooperation by exchanging data over communication networks. For this purpose, acoustic networks have been so far the choice par excellence. However, for operations involving vehicles operating at close range, there is currently a flurry of activity on the use of optical-based communication systems, capable of higher transmission rates. As a result, the goal of this work is to make optical communications viable and to use both communication technologies during underwater cooperative missions. Motivated by this goal, the first part of this work is dedicated to design a coordination controller with an event-based communication strategy for the coordination of the vehicles over the acoustic network. The second part of this work proposes an algorithm to make optical communications viable, which ultimately boils down to achieving optical beam alignment between a pair of cooperative agents. The proposed algorithm is illustrated by simulation results that show optical beam alignment being reached for a pair of vehicles in a cooperative formation.

关键词： Motion Control Cooperative Path Following Autonomous Underwater Vehicles Acoustic Optical Communication Event-Triggered Communications

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A New Recursive Composite Adaptive Controller for Robot Manipulators

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Space(Science & Technology) 2021年第1期2021卷 77-83页

作者： Jianfei Li Yaobing Wang Zhiyong Liu Xin Jing Chengwei Hu The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Beijing Key Laboratory of Intelligent Space Robotic System Technology and Applications Beijing Institute of Spacecraft System EngineeringBeijing 100094China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China

In this paper,a new recursive implementation of composite adaptive control for robot manipulators is *** investigate the recursive composite adaptive algorithm and prove the stability directly based on the Newton-Euler equations in matrix form,which,to our knowledge,is the first result on this point in the *** proposed algorithm has an amount of computation O(n),which is less than any existing similar algorithms and can satisfy the computation need of the complicated multidegree *** manipulator of the Chinese Space Station is employed as a simulation example,and the results verify the effectiveness of this proposed recursive algorithm.

关键词： Robot manipulators robot

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Saliency-SLAM: saliency prediction for visual SLAM

Saliency-SLAM: saliency prediction for visual SLAM

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Tianjin University-IET Electrical & Information engineering Doctoral Forum (TJU IET 2023)

作者： S. Jin Q. Meng Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin University Tianjin People's Republic of China

This paper proposes a novel approach for visual simultaneous localization and mapping (vSLAM), called Saliency-SLAM. This method effectively emulates the visual attention mechanism by integrating a saliency prediction model. In contrast to conventional vSLAM methods, which treat all feature points as equally significant, salient feature points are given greater importance in Saliency-SLAM. Therefore, we construct a novel saliency dataset specifically for vSLAM task to train a saliency prediction model by integrating multi-level visual information. Then, we propose to use the salient value of predicted result as the weight of significance for the feature points during the optimization process. Exhaustive experiments have been conducted on the KITTI dataset, demonstrating that our proposed method outperforms existing approaches in terms of localization accuracy.

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Trajectory-free dynamic locomotion using key trend states for biped robots with point feet

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Science China(Information Sciences) 2023年第8期66卷 263-264页

作者： Lianqiang HAN Xuechao CHEN Zhangguo YU Xishuo ZHU Kenji HASHIMOTO Qiang HUANG School of Mechatronical Engineering Beijing Institute of Technology Key Laboratory of Biomimetic Robots and Systems Ministry of Education Intelligent Mine Research Institute China Coal Research Institute Co. Ltd. Department of Mechanical Engineering Informatics Meiji University Humanoid Robotics Institute (HRI) Waseda University

Dear editor,Biped robots can not only cross complex environment such as ravines and rocks [1], but can also interact in more diverse activities with people. A biped robot with point feet is called an underactuated bip... 详细信息

关键词： Trajectories

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Reliability Design of Manipulator Joint for China Space Station 2

Reliability Design of Manipulator Joint for China Space Stat...

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2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2022

作者： Li, Delun Zhu, Chao Zhang, Yun Bai, Mei Huang, Zhipeng Xie, Zongwu Liu, Teng Fu, Hao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering CAST Beijing100094 China Beijing Satellite Manufacturing Co. Ltd. Beijing100094 China Beijing Institute of Space Environment Engineering Beijing100094 China

ISBN: (纸本)9781510657717

The TianHe manipulator is responsible for major tasks such as China Space Station construction, operation, and supporting astronaut's extravehicular operations. The joint is the direct execution part of the manipulator to realize flexible movement, and it is the key component to ensure the core functions and performance of the China Space Station manipulator, The composition of the joint is complex, and the experience of its reliability design is very poor. So the research of reliability design method for the joint is of great significance. Starting from the joint reliability design method, this paper uses various methods such as redundant design, margin design, and environmental adaptability design to complete the joint reliability design comprehensively. The ideas and methods for reliability design for the joint of the China Space Station manipulator introduced in this paper have important reference value for the reliability design for the space complicated electromechanical products. © 2022 SPIE. All rights reserved.

关键词： Space stations

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A Multi-Layer Software Architecture for Aerial Cognitive Multi-Robot systems in Power Line Inspection Tasks

arXiv

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arXiv 2023年

作者： Silano, Giuseppe Bednar, Jan Nascimento, Tiago Capitan, Jesus Saska, Martin Ollero, Anibal The Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic Department of Computer Systems Universidade Federal da Paraiba Brazil The GRVC Robotics Laboratory University of Seville Spain

This paper presents a multi-layer software architecture to perform cooperative missions with a fleet of quad-rotors providing support in electrical power line inspection operations. The proposed software framework guarantees the compliance with safety requirements between drones and human workers while ensuring that the mission is carried out successfully. Besides, cognitive capabilities are integrated in the multi-vehicle system in order to reply to unforeseen events and external disturbances. The feasibility and effectiveness of the proposed architecture are demonstrated by means of realistic simulations. Copyright © 2023, The Authors. All rights reserved.

关键词： Software architecture

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Deep Domain Adaptation Regression for Force Calibration of Optical Tactile Sensors

Deep Domain Adaptation Regression for Force Calibration of O...

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

作者： Zhuo Chen Ni Ou Jiaqi Jiang Shan Luo Department of Engineering Robot Perception Lab Centre for Robotics Research King’s College London London United Kingdom State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Optical tactile sensors provide robots with rich force information for robot grasping in unstructured environments. The fast and accurate calibration of three-dimensional contact forces holds significance for new sensors and existing tactile sensors which may have incurred damage or aging. However, the conventional neural-network-based force calibration method necessitates a large volume of force-labeled tactile images to minimize force prediction errors, with the need for accurate Force/Torque measurement tools as well as a time-consuming data collection process. To address this challenge, we propose a novel deep domain-adaptation force calibration method, designed to transfer the force prediction ability from a calibrated optical tactile sensor to uncalibrated ones with various combinations of domain gaps, including marker presence, illumination condition, and elastomer modulus. Experimental results show the effectiveness of the proposed unsupervised force calibration method, with lowest force prediction errors of 0.102N (3.4% in full force range) for normal force, and 0.095N (6.3%) and 0.062N (4.1%) for shear forces along the x-axis and y-axis, respectively. This study presents a promising, general force calibration methodology for optical tactile sensors.

关键词： Accuracy Force Tactile sensors Lighting Elastomers Data collection Optical imaging Adaptive optics Calibration Optical sensors

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Fault Diagnostic Opportunities for Electromagnetic Coils of Active Magnetic Bearings using Physics-of-Failure Analysis 5

Fault Diagnostic Opportunities for Electromagnetic Coils of ...

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5th International Conference on System Reliability and Safety engineering, SRSE 2023

作者： Li, Ruiqi Wang, Kai Zeng, Peng Cao, Jiwei Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang110016 China Harbin Institute of Technology Department of Electrical Engineering China

ISBN: (纸本)9798350305944

Active magnetic bearings (AMBs) have many advantages over traditional oil bearings due to their non-contact characteristics. They are environmentally friendly solution and have been proven to be highly reliable and available. Electromagnetic coils are vital components of AMB and they are failure prone. In this paper, the failure mode of magnetic bearing coil and its corresponding failure mechanism are reviewed by FMMEA method, and the existing coil fault diagnosis methods are introduced. Future directions for coil insulation health monitoring aiming at the application characteristics of AMBs are also discussed. © 2023 IEEE.

关键词： Failure analysis

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Design of a Small-Scale Locust-Inspired Robot Capable of Jump-gliding Locomotion

Design of a Small-Scale Locust-Inspired Robot Capable of Jum...

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IEEE International Conference on robotics and Biomimetics

作者： Weitao Zhang Zisen Wei Yi Xu Liang Peng Changwen Dong Yanzhou Jin Qing Shi 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

Small-scale robots are widely used in real-world rescue missions, but their mobility and movement range are still limited. One solution to improve their adaptability to complex environments is to introduce jumping and gliding strategies into the robot design. In this paper, we developed a small-scale locust-inspired robot capable of active (propeller-driven) gliding after launching from the ground, which had a body length of 19.1 cm and a weight of 97 g. On the basis of the locust’s musculoskeletal model, the jumping system was designed by a six-bar mechanism which can amplify the power. To improve the lift in gliding phase while reducing the draft in jumping phase, the gliding system with a folding wing and a front propeller was proposed corresponding to the fixed-wing principle. The results obtained through a series of experimental tests reveal that the robot achieves a jumping height of 0.15 m and a passive gliding distance of 1.5 m, which has a glide ratio of 1.13. Remarkably, actuating by a propeller, the robot can jump up to a height of 0.20 m, covering a gliding distance of 2.9 m. It is worth noting that the glide ratio of the robot improves by 91.2% in the propeller-driven jump-gliding mode.

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