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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Goran Vasiljević Dean Martinović Matko Batoš Stjepan Bogdan Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems University of Zagreb Zagreb Croatia

ISBN: (数字)9781665405935

ISBN: (纸本)9781665405942

In this paper we extend our previous work on UAV localization based on the magnetic field strength. The method is based on a magnetic flux density distribution in vicinity of two very long, thin and parallel transmission lines. An UAV is equipped with 4 magnetometers, positioned so that obtained measurements give unique solution to an optimization problem used to find relative position and orientation of the UAV with respect to conductors. Several sets of experiments, undertaken on a laboratory setup, confirmed validity of the method for both solutions - analytical and numerical optimization. Obtained results, compared with high precision motion capture system, are within range of standard RTK positioning.

关键词： Location awareness Magnetic field measurement Power measurement Magnetometers Current measurement Wires Transmission line measurements

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Modelling Autonomous Mobile Robot Interaction with IIoT Environments

Modelling Autonomous Mobile Robot Interaction with IIoT Envi...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Andrzej M.J. Skulimowski Wojciech Szulc Decision Science Laboratory AGH University Kraków Poland International Center for Decision Sciences and Forecasting Progress & Business Foundation Kraków Poland Automatic Control and Robotics AGH University

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

This article studies the deployment of autonomous robots in smart environments equipped with Industrial Internet of Things (IIoT) infrastructure. First, we characterize state-of-the-art IIoT solutions based on a bibliographic and openweb surveys, focusing on the interaction between autonomous robots and the IIoT infrastructures in the context of Robot-as-a-Service (RaaS) paradigm. Then, we define the criteria and requirements for optimal integration of a robot team equipped with an Internet of Vehicles (IoV) communication protocol with an existing IIoT. Sensors, edge devices, and data exchange algorithms are highlighted as crucial elements of seamless soft- and hardware integration. Establishing a quick interaction of robot decision-making algorithms with IIoT is seen as instrumental in identifying bottlenecks and vulnerabilities of the overall system, and a key to its desired performance. Another relevant issue is safety assurance of robot team in an IIoT environment as reflected in the appropriate standards that advocate responsible and sustainable technological progress in AI-enabled robotic systems. Finally, we will provide a real-life application example illustrating the principles and advantages of appropriate multirobot team integration in covered crops smart horticulture. This example pertains to the relevant area of Agricultural IoT (AIoT) applications, specifically focusing on the design of autonomous fruit-picking robots embedded in a greenhouse or polytunnel control infrastructures. Existing AIoT and crop control is integrated with robot software such as anticipatory coordination algorithms, world model building, navigation, and SLAM. Optimal integration is reached via a prior simulation with a dedicated Digital Twin application implemented in Matlab.

关键词： Performance evaluation Protocols Service robots Robot kinematics Mathematical models Safety Robots Standards Industrial Internet of Things Autonomous robots

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All-weather,natural silent speech recognition via machine-learning-assisted tattoo-like electronics

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npj Flexible Electronics 2021年第1期5卷 183-191页

作者： Youhua Wang Tianyi Tang Yin Xu Yunzhao Bai Lang Yin Guang Li Hongmiao Zhang Huicong Liu YongAn Huang State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhanChina Flexible Electronics Research Center Huazhong University of Science and TechnologyWuhanChina School of Mechanical and Electric Engineering Jiangsu Provincial Key Laboratory of Advanced RoboticsSoochow UniversitySuzhouChina State Key Laboratory of Industrial Control Technologyg Institute of Cyber Systems and ControlZhejiang UniversityHangzhouChina

The internal availability of silent speech serves as a translator for people with aphasia and keeps human–machine/human interactions working under various *** paper develops a silent speech strategy to achieve all-weather,natural *** strategy requires few usage specialized skills like sign language but accurately transfers high-capacity information in complicated and changeable daily *** the strategy,the tattoo-like electronics imperceptibly attached on facial skin record high-quality bio-data of various silent speech,and the machine-learning algorithm deployed on the cloud recognizes accurately the silent speech and reduces the weight of the wireless acquisition module.A series of experiments show that the silent speech recognition system(SSRS)can enduringly comply with large deformation(~45%)of faces by virtue of the electricitypreferred tattoo-like electrodes and recognize up to 110 words covering daily vocabularies with a high average accuracy of 92.64%simply by use of small-sample machine *** successfully apply the SSRS to 1-day routine life,including daily greeting,running,dining,manipulating industrial robots in deafening noise,and expressing in darkness,which shows great promotion in real-world applications.

关键词： translator weather silent

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A rolling bearing fault diagnosis method based on multi-source feature fusion

A rolling bearing fault diagnosis method based on multi-sour...

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Computer Information Science and Application Technology (CISAT), International Conference on

作者： Zhicheng Sun Qiushi Wang Yueming Zhu Dong Li Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of AutomationChinese Academy of Sciences Liaoning Province China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Shenyang Liaoning Province China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Liaoning Province China

ISBN: (数字)9798350375107

ISBN: (纸本)9798350375114

This paper presents a novel approach for fault diagnosis in rolling bearings using a multi-source feature fusion method. The proposed method aims to enhance the diagnostic accuracy by integrating both implicit and explicit features extracted from vibration data. Initially, one-dimensional Convolutional Neural Networks (1D CNNs) are employed to extract implicit features from the raw one-dimensional vibration signals. These features capture the complex patterns and correlations within the vibration data that are difficult to discern manually. Subsequently, explicit time-frequency domain features, such as mean and variance, are computed from the same vibration data. The implicit and explicit features are then fused to create a comprehensive feature representation that captures both the deeplevel patterns and the statistical properties of the vibration signals. The fused feature set is fed into a softmax classifier for fault classification. The performance of the proposed method is evaluated using the Case Western Reserve University (CWRU) bearing dataset, which contains various fault types and severity levels. Experimental results demonstrate that the proposed multi-source feature fusion approach achieves superior diagnostic accuracy compared to traditional methods that rely solely on either implicit or explicit features. The combination of 1D CNN-extracted implicit features and statistical explicit features provides a robust and effective solution for rolling bearing fault diagnosis.

关键词： Vibrations Fault diagnosis Time-frequency analysis Information science Accuracy Correlation Rolling bearings Feature extraction Data mining Machinery

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Research on the method of vision online distance measurement of laser holes in solar base cell

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International Journal of Wireless and Mobile Computing 2021年第2期20卷 179-190页

作者： Liu, Huaiguang Xiao, Wanghui Cai, Yu Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan Hubei430081 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan Hubei430081 China

To address the low efficiency of the current off-line laser hole distance method for solar cells (SC), an on-line distance measurement method of laser holes based on image processing is proposed. First, a forward irradiation imaging method with surface light is provided for the SC images. A line detection method of SC edge fitting is proposed and then the sub-pixel coordinates of feature points are obtained according to the laser point extraction algorithm based on the local area, and the distance between the laser hole and edge is calculated. Finally, the precise distance is obtained according to calibrated results between the pixel and millimetre. The experimental results show that this method can accurately measure the laser distances of SC holes, and is more accurate than the existing sub-pixel corner detection algorithm, which verifies the feasibility and accuracy of this method. Copyright © 2021 Inderscience Enterprises Ltd.

关键词： Computer vision

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Formation control of AUV on the Base of Visual Tracking of AUV-Leader

Formation Control of AUV on the Base of Visual Tracking of A...

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2021 International Russian Automation Conference, RusAutoCon 2021

作者： Filaretov, Vladimir Yukhimets, Dmitry Institute of Automation and Control Processes Feb Ras Robotics Laboratory Vladivostok Russia Institute of Marine Technology Problem Feb Ras Institute of Automation and Control Processes Feb Ras Vladivostok Russia

ISBN: (纸本)9780738131566

In this paper, a method for the synthesis of a group control system for AUV moving in the leader-follower mode was proposed. The position of the follower relative to the leader is proposed to be determined using an on-board video camera, which recognized the light beacons installed on the leader's body. The obtained information is used to form an estimate of the position of the target point in the coordinate system of the follower with a frequency sufficient for the implementation of high-precision robust control systems. A method for synthesizing a control system that provides a desired quality of control independently from changes in the parameters of the AUV-follower was proposed. The results of mathematical simulation confirmed the high quality of control provided by the proposed system. © 2021 IEEE.

关键词： Computer vision

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EgoEvGesture: Gesture Recognition Based on Egocentric Event Camera

arXiv

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arXiv 2025年

作者： Wang, Luming Shi, Hao Yin, Xiaoting Yang, Kailun Wang, Kaiwei Bai, Jian State Key Laboratory of Extreme Photonics and Instrumentation Zhejiang University China School of Robotics Hunan University China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University China

Egocentric gesture recognition is a pivotal technology for enhancing natural human-computer interaction, yet traditional RGB-based solutions suffer from motion blur and illumination variations in dynamic scenarios. While event cameras show distinct advantages in handling high dynamic range with ultra-low power consumption, existing RGB-based architectures face inherent limitations in processing asynchronous event streams due to their synchronous frame-based nature. Moreover, from an egocentric perspective, event cameras record data that includes events generated by both head movements and hand gestures, thereby increasing the complexity of gesture recognition. To address this, we propose a novel network architecture specifically designed for event data processing, incorporating (1) a lightweight CNN with asymmetric depthwise convolutions to reduce parameters while preserving spatiotemporal features, (2) a plug-and-play state-space model as context block that decouples head movement noise from gesture dynamics, and (3) a parameter-free Bins-Temporal Shift Module (BSTM) that shifts features along bins and temporal dimensions to fuse sparse events efficiently. We further establish the EgoEvGesture dataset, the first large-scale dataset for egocentric gesture recognition using event cameras. Experimental results demonstrate that our method achieves 62.7% accuracy tested on unseen subjects with only 7M parameters, 3.1% higher than state-of-the-art approaches. Notable misclassifications in freestyle motions stem from high interpersonal variability and unseen test patterns differing from training data. Moreover, our approach achieved a remarkable accuracy of 97.0% on the DVS128 Gesture, demonstrating the effectiveness and generalization capability of our method on public datasets. The dataset and models are made available at https://***/3190105222/EgoEv_Gesture. Copyright © 2025, The Authors. All rights reserved.

关键词： Gesture recognition

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Design of a Variable Stiffness Spring with Human-Selectable Stiffness

arXiv

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arXiv 2023年

作者： Mathews, Chase W. Braun, David J. Advanced Robotics and Control Laboratory within the Center for Rehabilitation Engineering and Assistive Technology Department of Mechanical Engineering Vanderbilt University NashvilleTN37235 United States

Springs are commonly used in wearable robotic devices to provide assistive joint torque without the need for motors and batteries. However, different tasks (such as walking or running) and different users (such as athletes with strong legs or the elderly with weak legs) necessitate different assistive joint torques, and therefore, springs with different stiffness. Variable stiffness springs are a special class of springs which can exert more or less torque upon the same deflection, provided that the user is able to change the stiffness of the spring. In this paper, we present a novel variable stiffness spring design in which the user can select a preferred spring stiffness similar to switching gears on a bicycle. Using a leg-swing experiment, we demonstrate that the user can increment and decrement spring stiffness in a large range to effectively assist the hip joint during leg oscillations. Variable stiffness springs with human-selectable stiffness could be key components of wearable devices which augment locomotion tasks, such as walking, running, and swimming. © 2023, CC BY-NC-ND.

关键词： Stiffness

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Lightweight Generative Adversarial Networks Based on Ghost Module

Lightweight Generative Adversarial Networks Based on Ghost M...

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2022 IEEE International Conference on Real-Time Computing and robotics, RCAR 2022

作者： Xiang, Xinyuan Liu, Meiqin Zhang, Senlin Wei, Ping Chen, Badong Xi'An Jiaotong University Institute of Artihcial Intelligence and Robotics Xi'an710049 China Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China Zhejiang University College of Electrical Engineering Hangzhou310027 China

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

Generative adversarial networks are widely used in computer vision tasks like image translation and image style transfer. Most of mainstream methods including CycleGAN and pix2pix use the stacking of residual blocks to deepen the number of network layers, which makes the networks have a large number of parameters and floating point operations. This paper presents a ghost-module-based generative adversarial networks. We use the ghost module to replace the residual blocks in the traditional generative adversarial network for building lightweight generative adversarial networks. Experiments shows that our method significantly reducing the parameters and floating point operations of the generative adversarial network on the precondition of assuring the quality of the generated images. © 2022 IEEE.

关键词： Generative adversarial networks

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Motion planning for highly-dynamic unconditioned reflexes based on chained Signed Distance Functions

arXiv

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arXiv 2025年

作者： Lin, Ken Ye, Qi Lam, Tin Lun Li, Zhibin Chen, Jiming Li, Gaofeng College of Control Science and Engineering Zhejiang University Hangzhou China Robotics and Artificial Intelligence Laboratory The Chinese University of Hongkong Shenzhen China Department of Computer Science University College London London United Kingdom

The unconditioned reflex (e.g., protective reflex), which is the innate reaction of the organism and usually performed through the spinal cord rather than the brain, can enable organisms to escape harms from environments. Accordingly, it is essential to endow robots the highly-dynamic unconditioned reflexes to humans and/or environments, such that it can work collaboratively with humans or serve people in daily life. Although various sampling-based and optimization-based motion planning methods have been developed for robots, their limited computational speed is not suitable for rapid motion planning in highly-dynamic environments. In this paper, we propose an online, highly-dynamic motion planning algorithm to enable highly-dynamic unconditioned reflexes for manipulators. Our method is based on a chained version of Signed Distance Functions (SDFs), which can be pre-computed and stored. Our proposed algorithm is divided into two stages. In the offline stage, we create 3 groups of local SDFs to store the geometric information of the manipulator and its working environment. The SDFs in the first group are to describe the geometric information of the static environment. The SDFs in the second group are to describe the geometric information of each link. While the SDFs in the last group are to describe the reachability of each link’s end of the manipulator. In the online stage, the precomputed local SDFs are chained together according the configuration of the manipulator, to provide global geometric information about the environment. While the point clouds of the dynamic objects serve as query points to look up these local SDFs for quickly generating escape velocity. Then we propose a modified geometric Jacobian matrix and use the Jacobian-pseudo-inverse method to generate real-time reflex behaviors to avoid the static and dynamic obstacles in the environment. The benefits of our method are validated in both static and dynamic scenarios. In the static scenario, our meth

关键词： Jacobian matrices

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