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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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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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LiDAR-based drone navigation with reinforcement learning

TechRxiv

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TechRxiv 2023年

作者： Miera, Pawel Szolc, Hubert Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland

Reinforcement learning is of increasing importance in the field of robot control and simulation plays a key role in this process. In the unmanned aerial vehicles (UAVs, drones), there is also an increase in the number of published scientific papers involving this approach. In this work, an autonomous drone control system was prepared to fly forward (according to its coordinates system) and pass the trees encountered in the forest based on the data from a rotating LiDAR sensor. The Proximal Policy Optimization (PPO) algorithm, an example of reinforcement learning (RL), was used to prepare it. A custom simulator in the Python language was developed for this purpose. The Gazebo environment, integrated with the Robot Operating System (ROS), was also used to test the resulting control algorithm. Finally, the prepared solution was implemented in the Nvidia Jetson Nano eGPU and verified in the real tests scenarios. During them, the drone successfully completed the set task and was able to repeatably avoid trees and fly through the forest. © 2023, CC BY.

关键词： Drones

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Human-Robot Pose Tracking Based on CNN with Color and Geometry Aggregation 16th

Human-Robot Pose Tracking Based on CNN with Color and Geo...

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16th International Conference on Social robotics, ICSR + InnoBiz 2024

作者： Xu, Yue Zhang, Yinlong Liu, Shuai Liu, Yuanhao Liang, Wei He, Hongsheng Shenyang University of Technology Shenyang110020 China Guangzhou Institute of Industrial Intelligence Guangzhou511458 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Department of Computer Science The University of Alabama TuscaloosaAL35487 United States

ISBN: (纸本)9789819611508

Accurately tracking the robotic arm and human joints is crucial to ensure safety during human-robot interaction. However, traditional pose tracking methods often exhibit insufficient performance and robustness in complex environments. The variations in the robotic arm’s environment and posture make it challenging for traditional methods to accurately capture the positions and posture of its joints. Specifically, when addressing challenges such as high similarity, occlusion, background complexity, and joint recognition failures, they often struggle to provide reliable and accurate results. To address these challenges, this paper proposes a human-robot pose tracking algorithm based on a new convolutional neural network model. To enhance detection accuracy, an improved color detection module is introduced to resolve joint misclassification. A geometric perception module is designed to accurately locate joints even under occlusion. Additionally, innovative iEMA and DBB modules are incorporated. The iEMA module employs edge detection technology to dynamically adjust thresholds for correct matching by improving the edge matching process. The DBB module refines the boundary box parameters for precise localization by introducing adaptive bounding box updates in real-time. This algorithm also integrates human pose recognition, enabling real-time pose recognition, thereby facilitating more intelligent and natural human-robot interaction. The algorithm has been rigorously evaluated on a custom-designed robotic arm platform. Experimental results validate the algorithm’s effectiveness and feasibility. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Robotic arms

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Distributed Event-Triggered Formation control for a Multi-robotic Fish System

Distributed Event-Triggered Formation Control for a Multi-ro...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Dai, Shijie Wu, Zhengxing Tan, Min Yu, Junzhi School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China State Key Laboratory for Turbulence and Complex System Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Peking University Beijing100871 China

ISBN: (纸本)9789811966125

This paper investigates the formation control problem for a multi-robotic fish system and a distributed event-triggered-based formation control framework is proposed. The framework consists of a communication topology, a distributed formation control law, and a dynamic event-triggered communication mechanism. In particular, a position-based formation control law is presented to drive the multi-robotic fish system to an anticipated configuration based on local measurements while keeping pace with a moving target. Meanwhile, a dynamic event-triggered mechanism is utilized to measure importance of the interactive information and decide the communication timing. The proposed formation control method shows its merits to greatly reduce communication consumption with a limited loss of formation control performance. Finally, simulations with quantitative comparisons are presented to verify the effectiveness of the proposed framework. This formation control framework provides a solid foundation for future marine cooperative control of the multi-robotic fish system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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LiDAR-based drone navigation with reinforcement learning

arXiv

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arXiv 2023年

关键词： Robot Operating System

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Substantiation of Probability Characteristics for Efficiency Analysis in the Process of Radio Equipment Diagnostics 3

Substantiation of Probability Characteristics for Efficiency...

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3rd IEEE Ukraine Conference on Electrical and Computer Engineering, UKRCON 2021

作者： Solomentsev, Oleksandr Zaliskyi, Maksym Yashanov, Ivan Shcherbyna, Olga Sushchenko, Olha Yanovsky, Felix Ostroumov, Ivan Averyanova, Yuliya Kuzmenko, Nataliia National Aviation University Department of Telecommunication and Radioelectronic Systems Kyiv Ukraine National Aviation University Department of Electronics Robotics Monitoring and IoT Technologies Kyiv Ukraine National Aviation University Aerospace Control Systems Department Kyiv Ukraine National Aviation University Air Navigation Systems Department Kyiv Ukraine

ISBN: (纸本)9781665400947

The paper discusses the problem of statistical characteristics substantiation during radio equipment diagnostics. To provide serviceability and maintainability of radio equipment is one of the tasks of operation system. The operation system contains the processes of intended use of equipment, maintenance, running repair, continuation of life service and others. During running repair, the procedures of diagnostics, operability recovery and parameters monitoring are performed. The diagnostics process regulates the sequence of searching the failed element in the radio equipment scheme. The decision-making during diagnostics is associated with the errors of the first and second kind. So for efficiency analysis, the probability of correct diagnostics can be used. Such efficiency measure has random nature, but in the literature, only expected value is used to describe it. This paper concentrates on the approach to calculation of the probability density function for efficiency measure with purpose of obtaining the complete information about random value. © 2021 IEEE.

关键词： Probability

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Self-Tuning Robust Tracking control for Autonomous Underwater Vehicles

Self-Tuning Robust Tracking Control for Autonomous Underwate...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Nima Maghooli Fahimeh S. Tabatabaee-Nasab S. Ali A. Moosavian Department of Mechanical Engineering Center of Excellence in Robotics and Control Advanced Robotics … Automated Systems (ARAS) Laboratory K. N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781665454537

This paper addresses the control design problem for a nonlinear and nonholonomic dynamics model of an autonomous underwater vehicle. The kinematics control algorithm is a PID controller while a self-tuning control method is used for trajectory tracking. The kinetics control algorithm is based on an integral sliding mode technique that is robust against time-varying disturbances. The obtained results presented here use the Remote Environmental Monitoring UnitS (REMUS) underwater vehicle model and show the high performance of the controller. Based on the results demonstrated for the two designated trajectories, the tracking quality of self-tuning robust control, despite the significant similarity of the control input of both algorithms for x, y, and z, is much better than the sliding mode control. As a result, AUV was able to follow the desired trajectory, and tracking errors converged to zero. It is worth noting that at non-derivative points of the path (1 st trajectory), tracking errors were entirely within response quality limits (y = ±0.05[m]). The order of control efforts of the proposed control is suitable and can be implemented in the physical system.

关键词： Robust control Autonomous underwater vehicles Mechatronics Trajectory tracking Heuristic algorithms Robot kinematics Trajectory

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SLAM-Based Joint Calibration of Differential RSS Sensor Array and Source Localization 49

SLAM-Based Joint Calibration of Differential RSS Sensor Arra...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Fu, Linya Qiao, Xu Huang, Shoudong Mao, Guoqiang Lin, Zhiyun Li, Youfu Kong, He Robotics Institute Uni. of Technology Sydney Sydney Australia Xidian University State Key Laboratory of Integrated Services Networks China City University of Hong Kong Department of Mechanical Engineering China Southern Uni. of Sci. and Tech. Shenzhen Key Laboratory of Control Theory and Intelligent Systems Shenzhen China Southern Uni. of Sci. and Tech. Guangdong Prov. Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Shenzhen China

ISBN: (纸本)9798350331820

Sensor arrays generating differential received signal strength (DRSS) measurements have found many applications in robotics. However, accurate calibration of these sensor arrays remains a challenge. Most existing methods are impractical in that they assume to know signal source positions or certain parameters (i.e., path loss exponent), and try to estimate the others. In this paper, we adopt graph simultaneous localization and mapping (SLAM) as a general framework for jointly estimating the source positions and parameters of the DRSS sensor array. Our contributions are twofold. On the one hand, by using a Fisher information matrix approach, we conduct a systematic observability analysis of the corresponding SLAM setup for the calibration problem. On the other hand, we propose an effective procedure to select the initial value which is fed to Levenberg-Marquardt iterations for further improving optimization accuracy and convergence. Extensive simulation and hardware experiments show that the proposed method renders high-quality calibration results. All the codes and data are publicly available at https://***/SUSTech2022/DRSS-sensor-array-calibration. © 2023 IEEE.

关键词： Calibration

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Sequential method of reliability parameters estimation for radio equipment 12

Sequential method of reliability parameters estimation for r...

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12th IEEE International Conference on Electronics and Information Technologies, ELIT 2021

作者： Zaliskyi, Maksym Solomentsev, Oleksandr Kuzmenko, Nataliia Yanovsky, Felix Shcherbyna, Olga Sushchenko, Olha Ostroumov, Ivan Averyanova, Yuliya Department of Telecommunication and Radioelectronic Systems National Aviation University Kyiv Ukraine Air Navigation Systems Department National Aviation University Kyiv Ukraine Department of Electronics Robotics Monitoring and IoT Technologies National Aviation University Kyiv Ukraine Aerospace Control Systems Department National Aviation University Kyiv Ukraine

ISBN: (纸本)9781665442961

Radio equipment for aircraft flight supporting consists of communication, navigation and surveillance devices. These devices are used to provide the safety and regularity of aircraft flights. During radio equipment operation the processes of intended use, maintenance, repair, continuation of life service are implemented. The decision-making about control and preventive actions for these processes is based on the results of statistical data processing. In such cases statistical methods with predetermined sample size are used. This paper concentrates on the problem of synthesis of sequential method that allows making decision faster for given level of data processing effectiveness. The researched sequential method is used for estimation of reliability parameters based on priory information about these parameters distribution and functional transformation of corresponding probability density function. During solving analysis problem, the probability density functions of estimate and observation duration are calculated. © 2021 IEEE.

关键词： Probability density function

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