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Dynamic Movement Primitives Based robot Skills Learning

Machine Intelligence Research 2023年第3期20卷 396-407页

作者： Ling-Huan Kong Wei He Wen-Shi Chen Hui Zhang Yao-Nan Wang School of Intelligence Science and Technology University of Science and Technology BeijingBeijing 100083China Institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China School of Robotics and the National Engineering Laboratory of Robot Visual Perception and Control Technology Hunan UniversityChangsha 410082China

In this article,a robot skills learning framework is developed,which considers both motion modeling and *** order to enable the robot to learn skills from demonstrations,a learning method called dynamic movement primitives(DMPs)is introduced to model motion.A staged teaching strategy is integrated into DMPs frameworks to enhance the generality such that the complicated tasks can be also performed for multi-joint *** DMP connection method is used to make an accurate and smooth transition in position and velocity space to connect complex motion *** addition,motions are categorized into different goals and *** is worth mentioning that an adaptive neural networks(NNs)control method is proposed to achieve highly accurate trajectory tracking and to ensure the performance of action execution,which is beneficial to the improvement of reliability of the skills learning *** experiment test on the Baxter robot verifies the effectiveness of the proposed method.

关键词： Dynamic movement primitives(DMPs) trajectory tracking control robot learning from demonstrations neural networks(NNs) adaptive control

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Trajectory tracking control for nonlinear high-order PDE system based on iterative learning method 38

Trajectory tracking control for nonlinear high-order PDE sys...

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38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Liu, Yaqiang Zhang, Weili Peng, Jinzhu Zhang, Wenlong Liu, Yanhong Zhengzhou University Henan Senyuan Electric Co. Ltd. School of Electrical and Information Engineering Zhengzhou China Zhengzhou University Sch. of Elec. and Info. Eng. Robot Perception and Control Engineering Laboratory of Henan Province Zhengzhou China Zhengzhou University School of Electrical and Information Engineering Zhengzhou China

ISBN: (纸本)9798350303636

This paper addresses a trajectory tracking control method based on iterative learning for the nonlinear fourth-order partial differential equation (PDE) system. A noval iterative learning control law is designed that enables the repeatable Kuramoto-Sivashinsky equation system track the desired trajectory. The Poincar'e-Wirtinger inequality and Cauchy-Schwartz inequality are applied to deal with the function problem in this paper. By using the Gronwall-Bellman lemma and integration by parts technique, a Lyapunov function is constructed and an LMI sufficient condition is provided, respectively. The effectiveness of the proposed iterative learning control method is verified through the convergence proof of the closed-loop Kuramoto-Sivashinsky equation system. Finally, the trajectory tracking curve simulation after multiple iterations is provied in this paper. © 2023 IEEE.

关键词： convergence analysis iterative learning control multiple actuators and sensors nonlinear high-order PDE system

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Adaptive Safety control of a Constrained Uncertain robotic System 8

Adaptive Safety Control of a Constrained Uncertain Robotic S...

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8th International Conference on Automation, control and robotics engineering, CACRE 2023

作者： Wang, Haijing Peng, Jinzhu Zhang, Fangfang Wang, Yaonan School of Electrical and Information Engineering Zhengzhou University Zhengzhou China National Engineering Laboratory for Robot Visual Perception and Control Hunan University Changsha China College of Electrical and Information Engineering Hunan University Changsha China

ISBN: (纸本)9798350302776

The safety control problem of a constrained uncertain robotic system is investigated in this paper. First, the high-order control barrier functions (HoCBFs) are introduced to deal with the output constraints for he system. And to solve the uncertain problem and revisit the HoCBF-based framework, an adaptive approach is proposed to updating the unknown parameters online. In this way, the system safety can be achieved adaptively by keeping the system output within the predefined constrained region even in the presence of parametric uncertainty. Finally, simulation tests are carried out to verify the validity of the proposed controller. © 2023 IEEE.

关键词： Uncertainty analysis

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Resilient Formation control Based on Watermarks for Networked Quadrotors under Deception Attacks

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IEEE Transactions on Vehicular Technology 2025年第6期74卷 8839-8850页

作者： Zhan, Weiwei Miao, Zhiqiang Zeng, Jianxin Chen, Yanjie Wu, Zheng-Guang He, Wei Wang, Yaonan Hunan University College of Electrical and Information Engineering Changsha410082 China Fuzhou University School of Mechanical Engineering and Automation Fuzhou350108 China National Engineering Research Center of Robot Visual Perception and Control Technology Changsha410082 China Zhejiang University Institute of Cyber-Systems and Control Hangzhou310027 China University of Science and Technology Beijing Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of Education School of Intelligence Science and Technology Institute of Artificial Intelligence Beijing100083 China

This article addresses the problem of formation control of networked UAVs under deception attacks. A lightweight resilient formation control framework based on watermarks is proposed to achieve the desired formation configuration without extra monitoring attack status. Since deception attacks are covert, the shared information is watermarked before transmission to establish the protocol among networked UAVs. To facilitate the resilient formation controller design, a decoder is first developed to decipher the inverse transformation of deception attacks, where the watermark is the criterion for approximating the inverse transformation. The Gauss error function is introduced to eliminate some unrealistic input commands under deception attacks, obtaining the predefined input performance. Then, a resilient formation controller is developed to guarantee the global boundedness of all signals within the inner-loop and outerloop system, while the formation error converges to a small neighborhood of zero by solving the linear matrix inequality. Two challenging deception attack examples in simulations and experiments are conducted to verify the effectiveness and performance of the proposed resilient formation control framework. © 1967-2012 IEEE.

关键词： Inverse transforms

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Insulator Fault Diagnosis Based on Improved Transfer Learning from UAV Images

Insulator Fault Diagnosis Based on Improved Transfer Learnin...

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Yang, Lei Shen, Ji Wu, Man Liu, Yanhong Zhengzhou University School of Electrical Engineering 450001 China Robot Perception and Control Engineering Laboratory of Henan Province 450001 China Beijing Aerospace Control Center P.O.Box 5130 118 points boxes Haidian District Beijing China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Insulator fault diagnosis is a daily but key task for the power transmission system. Long-term exposure to complex natural environment will cause different insulator defects. As a common defects, missing-cap defects of insulators will not only affect the structural strength of power insulators, but also bring a certain effect to the stable power transmission. With the rapid development of machine learning, some machine learning-based defect recognition methods have been proposed for fast and high-precision power inspection. However, the handcrafted features could not effectively express the aerial images against complex inspection environment to affect detection performance of the shallow learning algorithms. And the detection precision of deep learning algorithms will be affected by the unbalanced small-scale defects. Therefore, the fast and high-precision power inspection still faces a certain challenge in the smart grid. To address the above issues, fusion with the deep convolutional neural network (DCNN) and transfer learning, a novel fault diagnosis algorithm of power insulators is proposed to provide a fast and accurate power inspection scheme. To remove complex backgrounds, a fast insulator location algorithm based on the lightweight YOLOV4 model is proposed which is served for the following defect recognition. On the basis, to imitate human vision, a defect recognition algorithm is proposed based on multi-feature fusion. Meanwhile, to ensure the feature expression ability of transfer learning on power insulators, a novel optimization strategy of transfer learning is proposed to improve the recognition precision. Experiments show that the proposed method could acquire a good recognition performance than other recognition models. © 2022 IEEE.

关键词： Inspection

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High Dynamic Range 3d Measurement with Adaptive Projection Pattern Generated from Saturated Image

SSRN

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SSRN 2024年

作者： Yu, Hongshan Liang, Xianqiang Yu, Ruiming Xu, Haiqiang Sun, Wei National Engineering Laboratory for Robot Visual Perception and Control Technology College of Electrical and Information Engineering Hunan University Changsha China

Fringe projection profilometry (FPP) shows the advantages of high efficiency and high accuracy in distance sensing. However, it is prone to measurement errors due to fringe saturation in high dynamic range (HDR) scenes. Popular adjust projection intensity (API) based FPP methods have been proposed to reduce the influence of reflectivity variance. Because existing API based FPP method depend on unsaturated images to generate adaptive projection patterns, its measurement time is increased. In this paper, we propose a high dynamic range 3D measurement method with adaptive projection pattern generated from saturated image. Firstly, we establish the reflectance relationship between unsaturated region and saturated region to compute adaptive projection intensity, which removes the dependence of unsaturated images. Secondly, we improve measurement efficiency in computation process by recycling the captured images. In addition, we propose a capture intensity correction method to remove the effect of light propagation distance. Experiments prove that the proposed method has significant advantages in a variety of HDR scenes. Compared with linear-API method, proposed method improves the measurement accuracy by 15.59%. Meanwhile, the number of projection patterns is reduced by 40% compared to the method which based on multiple exposure fusion image (MEFI). © 2024, The Authors. All rights reserved.

关键词： Reflection

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Single Domain Generalization in Vibration Damper Detection Using Frequency Domain Attention and Scale-Invariant Learning

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IEEE Transactions on Power Delivery 2025年

作者： Yang, Ke Zhao, Xiaoyu Ge, Xinyu Hu, Zhedong Wang, Qianming Zhai, Yongjie North China Electric Power University School of Control and Computer Engineering Baoding071003 China Baoding Key Laboratory of Intelligent Robot Perception and Control in Electric Power System Baoding China

Improving the generalization capability of vibration damper detection model for transmission lines is essential for its application in complex power scenarios. Variations in vibration damper types, and unmanned aerial vehicle(UAV) shooting distances lead to domain shift, which impacts detection performance. This paper proposes a single domain generalization (SDG) detection method for vibration dampers that integrates structural knowledge to guide the model in extracting domaininvariant features (DIF), combining frequency domain attention (FDA) and scale-invariant learning (SIL). Different types of vibration dampers exhibit combinatory structural invariance, while dampers of varying scales demonstrate aspect ratio invariance. First, a learnable weight matrix is applied to the amplitude spectrum after Fourier transformation, preserving low-frequency information while attenuating high-frequency components. This approach retains structural features and reduces morphological differences. Next, SIL is introduced to emphasize aspect ratios during bounding box regression, improving the model's capacity to handle scale variations and enhancing feature generalization. Experimental results demonstrate that without significantly increasing the number of parameters and model size, the proposed method achieves AP50 of 60.8% and 77.1% in the two target domains, respectively, representing increases of 3.3% and 4.0% over the original model, thus offering strong support for the practical application of intelligent detection models. © 1986-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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NCV-PWM Method for the Phase Current Reconstruction With DC Link Single Sensor

NCV-PWM Method for the Phase Current Reconstruction With DC ...

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作者： Shen, Yongpeng Wu, Kexuan Yuan, Xiaofang Wu, Chengzhong Liang, Weihua Chen, Zhiwei The College of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou450002 China The Department of Electric and Information Engineering Hunan University Changsha410082 China The National Engineering Laboratory for Robot Visual Perception and Control Technology Hunan University Changsha410082 China

The DC link current sampling with a single sensor is a promising solution in the electric drive field due to its low cost and small volume. However, limited by the minimum sampling time, the current reconstruction unobservable area is the most intractable challenge in the traditional single sensor reconstruction method, especially in sector boundary areas, where the phase current cannot be reconstructed completely. In this article, a new non-zero compensation vector pulse width modulation (NCV-PWM) method is proposed to eliminate the current unobservable area. Firstly, by introducing the definition of minimum sampling time, the voltage space vector plane is accurately divided into different modulation areas. Then, by applying non-zero compensation vector in the sector boundary, the current sampling window is extended, and the sampling time requirement for the DC link current is satisfied. Finally, the practicability and accuracy of the NCV-PWM method are verified by experiments, and results show that the current reconstruction error is less than 2.86%, which provides accurate current feedback for high-performance motor control. © 2023 IEEE.

关键词： Electric drives

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An Efficient Generative Intelligent Multiobjective Grasping Model for Kitchen Waste Sorting

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Deng, Songyun Pei, Ruiyuan Zhou, Li Qin, Hai Sun, Wei Liang, Qiaokang Hunan University College of Electrical and Information Engineering Changsha410082 China Hunan University National Engineering Laboratory for Robot Vision Perception and Control College of Electrical and Information Engineering Changsha410082 China

The key challenge in automated kitchen waste sorting on conveyor belts is how robots execute grasping tasks. Current methods, dependent on object detection, struggle to adopt generative architectures due to data scarcity and algorithmic inefficiency. To solve these issues, this article proposes solutions in three aspects: dataset construction, annotation data processing, and generative model lightweighting. First, we built the KWG2024 dataset, which includes 3116 RGB-D images, 18231 standard annotations, and three new evaluation metrics. Second, we proposed two novel annotation processing methods to address the issue of excessive and incorrect grasps generated by generative networks in single-attempt grasp planning of multiobjects. Third, we constructed an efficient network with classification capabilities, AMI-LiteNet, by integrating the advantages of PP-LiteSeg and AMI-NanoNet. On the public Cornell dataset, AMI-LiteNet achieved a grasping accuracy of 98.3% and an efficiency of 118 frames per second (FPS). In extensive comparative experiments on KWG2024, our model reached a leading computational efficiency compared with recent state-of-the-art methods. It acquired a grasp planning generation accuracy of 87.96% while only requiring a computational effort of 2.79 GFLOPs. Finally, our model was deployed on an edge computing device and achieved a maximum grasping accuracy of 90.91% and a classification accuracy (CA) of 97.48% in our actual robotic system. To our knowledge, this is the first time that a generative grasp method has been applied independently to kitchen waste sorting tasks on a conveyor belt. © 1963-2012 IEEE.

关键词： Belt conveyors

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Boundary Gap Based Reactive Navigation in Unknown Environments

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IEEE/CAA Journal of Automatica Sinica 2021年第2期8卷 468-477页

作者： Zhao Gao Jiahu Qin Shuai Wang Yaonan Wang the Department of Automation University of Science and Technology of ChinaHefei 230027China the College of Electrical and Information Engineering Hunan UniversityChangsha 410082 the National Engineering Laboratory for Robot Visual Perception and Control Technology Changsha 410082China

Due to the requirements for mobile robots to search or rescue in unknown environments,reactive navigation which plays an essential role in these applications has attracted increasing ***,most existing reactive methods are vulnerable to local minima in the absence of prior knowledge about the *** paper aims to address the local minimum problem by employing the proposed boundary gap(BG)based reactive navigation ***,the narrowest gap extraction algorithm(NGEA)is proposed to eliminate the improper ***,we present a new concept called boundary gap which enables the robot to follow the obstacle boundary and then get rid of local ***,in order to enhance the smoothness of generated trajectories,we take the robot dynamics into consideration by using the modified dynamic window approach(DWA).Simulation and experimental results show the superiority of our method in avoiding local minima and improving the smoothness.

关键词： Boundary gap local minima reactive navigation unknown environments

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