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High-Order control Barrier Function-Based Safety control of Constrained robotic Systems:An Augmented Dynamics Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2487-2496页

作者： Haijing Wang Jinzhu Peng Fangfang Zhang Yaonan Wang the School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China the National Engineering Laboratory for Robot Visual Perception and Control Hunan UniversityChangsha 410082China the College of Electrical and Information Engineering Hunan UniversityChangsha 410082China

Although constraint satisfaction approaches have achieved fruitful results,system states may lose their smoothness and there may be undesired chattering of control inputs due to switching ***,it remains a challenge when there are additional constraints on control torques of robotic *** this article,we propose a novel high-order control barrier function(HoCBF)-based safety control method for robotic systems subject to input-output constraints,which can maintain the desired smoothness of system states and reduce undesired chattering vibration in the control *** our design,augmented dynamics are introduced into the HoCBF by constructing its output as the control input of the robotic system,so that the constraint satisfaction is facilitated by HoCBFs and the smoothness of system states is maintained by the augmented *** proposed scheme leads to the quadratic program(QP),which is more user-friendly in implementation since the constraint satisfaction control design is implemented as an add-on to an existing tracking control *** proposed closed-loop control system not only achieves the requirements of real-time capability,stability,safety and compliance,but also reduces undesired chattering of control ***,the effectiveness of the proposed control scheme is verified by simulations and experiments on robotic manipulators.

关键词： Augmented dynamics high-order control barrier function(HoCBF) input-output constraints quadratic program(QP) robotic systems

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SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo

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IEEE Transactions on Circuits and Systems for Video technology 2025年第6期35卷 5724-5737页

作者： Yin, Yufeng Liu, Xiaoyan Zhang, Zichao Hunan University National Engineering Laboratory for Robot Visual Perception and Control Technology College of Electrical and Information Engineering Changsha410082 China Innovation Institute of Industrial Design and Machine Intelligence Quanzhou-Hunan University Quanzhou362006 China

Multi-view stereo aims to recover the 3D model of a scene from a set of images. However, low-textured areas in the scene have always been a challenge in 3D reconstruction. In this work, we propose a segmentation-guided multi-scale anchor deformation patch multi-view stereo. Specifically, we use the Segment Anything Model to distinguish different instances in the scene, and propose an anchor deformation strategy guided by segmentation to adaptively generate a multi-scale anchor patch, so that the depth can be refined from coarse to fine scales. To propagate a better hypothesis for low-textured areas where photometric consistency is unreliable, we propose a non-local adaptive propagation scheme by using the segmented mask as a propagation domain. In order to reduce the interference of illumination on reconstruction completeness, we propose an outlier depth cost refinement guided by reliable points that improves the performance of depth estimation in unevenly illuminated areas. As a result, our method achieves state-of-the-art performance among traditional methods and exhibits better generalization capabilities on the ETH3D, Tanks and Temples, and DTU datasets. © 1991-2012 IEEE.

关键词： Image segmentation

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Adaptive control of a Flexible Manipulator With Unknown Hysteresis and Intermittent Actuator Faults

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 148-158页

作者： Shouyan Chen Weitian He Zhijia Zhao Yun Feng Zhijie Liu Keum-Shik Hong School of Mechanical and Electrical Engineering Guangzhou University the School of Control Science and Engineering Shandong University IEEE the College of Electrical and Information Engineering Hunan University the National Engineering Research Center for Robot Visual Perception and Control Technology Hunan University the School of Intelligence Science and Technology University of Science and Technology Beijing (USTB) the Institute for Future the School of AutomationQingdao University the School of Mechanical Engineering Pusan National University

In this study, we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults. First, an inverse hysteresis dynamics model is introduced, and then the control input is divided into an expected input and an error compensator. Second,a novel adaptive neural network-based control scheme is proposed to cancel the unknown input hysteresis. Subsequently,by modifying the adaptive laws and local control laws, a fault-tolerant control strategy is applied to address uncertain intermittent actuator faults in a flexible manipulator system. Through the direct Lyapunov theory, the proposed scheme allows the state errors to asymptotically converge to a specified interval. Finally,the effectiveness of the proposed scheme is verified through numerical simulations and experiments.

关键词： Adaptive control flexible manipulator intermittent actuator faults inverse hysteresis dynamics vibration control

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Vision-Based Leader-Follower Formation control for Mobile robots 24

Vision-Based Leader-Follower Formation Control for Mobile Ro...

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2nd International Conference on Artificial Intelligence, Systems and Network Security, AISNS 2024

作者： Wan, Qin Ning, Shunxing Xu, Pin Li, Zhi Hunan Institute of Engineering Hunan Xiangtan China National Engineering Research Center for Robot Visual Perception and Control Technology Hunan Changsha China

ISBN: (纸本)9798400711237

This paper proposes a vision-based formation control method for multi-robot systems in the absence of inter-robot communication, employing a leader-follower scheme with a single Kinect camera as the sole sensor. By utilizing a pose estimation algorithm based on RGBD images, the relative position and orientation of the leader are captured. An anticipated formation shape aligned in the same movement direction is generated using a dipole vector field, ensuring formation stability. To address the limited field of view of the Kinect camera, an auxiliary system is designed to transform visibility constraints into input constraints, enabling effective control under non-communicative conditions. Simulation and experimental results demonstrate that the proposed method achieves real-time and robust formation control despite visibility limitations, simplifying the system architecture and enhancing practicality. © 2024 Copyright held by the owner/author(s).

关键词： Mobile robots

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OAFuser: Toward Omni-Aperture Fusion for Light Field Semantic Segmentation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6225-6239页

作者： Teng, Fei Zhang, Jiaming Peng, Kunyu Wang, Yaonan Stiefelhagen, Rainer Yang, Kailun Hunan University School of Robotics National Engineering Research Center of Robot Visual Perception and Control Technology Changsha410082 China Karlsruhe Institute of Technology Institute for Anthropomatics and Robotics Karlsruhe76131 Germany Institute for Visual Computing ETH Zurich Zurich8092 Switzerland

Light field cameras are capable of capturing intricate angular and spatial details. This allows for acquiring complex light patterns and details from multiple angles, significantly enhancing the precision of image semantic segmentation. However, two significant issues arise: 1) The extensive angular information of light field cameras contains a large amount of redundant data, which is overwhelming for the limited hardware resources of intelligent agents. 2) A relative displacement difference exists in the data collected by different microlenses. To address these issues, we propose an omni-aperture fusion model (OAFuser) that leverages dense context from the central view and extracts the angular information from subaperture images to generate semantically consistent results. To simultaneously streamline the redundant information from the light field cameras and avoid feature loss during network propagation, we present a simple yet very effective subaperture fusion module (SAFM). This module efficiently embeds subaperture images in angular features, allowing the network to process each subaperture image with a minimal computational demand of only (∼1\rm GFlops). Furthermore, to address the mismatched spatial information across viewpoints, we present a center angular rectification module (CARM) to realize feature resorting and prevent feature occlusion caused by misalignment. The proposed OAFuser achieves state-of-the-art performance on four UrbanLF datasets in terms of all evaluation metrics and sets a new record of 84.93% in mIoU on the UrbanLF-Real Extended dataset, with a gain of +3.69%. The source code for OAFuser is available at https://***/FeiBryantkit/OAFuser. © 2020 IEEE.

关键词： Semantic Segmentation

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Differentiable Automatic Data Augmentation by Proximal Update for Medical Image Segmentation

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1315-1318页

作者： Wenxuan He Min Liu Yi Tang Qinghao Liu Yaonan Wang College of Electrical and Information Engineering Hunan UniversityChangsha 410082 National Engineering Research Center of Robot Visual Perception and Control Technology Changsha 410082China

Dear editor,This letter presents an automatic data augmentation algorithm for medical image *** increase the scale and diversity of medical images,we propose a differentiable automatic data augmentation algorithm based on proximal update by finding an optimal augmentation ***,on the one hand,a dedicated search space is designed for the medical image segmentation *** the other hand,we introduce a proximal differentiable gradient descent strategy to update the data augmentation policy,which would increase the searching *** of the experiments indicate that the proposed algorithm significantly outperforms state-of-the-art methods,and search speed is 10 times faster than state-of-the-art methods.

关键词： editor policy Image

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Self-Contrastive Learning Fault Diagnosis Network for Signal Imaging: A Case Study

Self-Contrastive Learning Fault Diagnosis Network for Signal...

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2024 China Automation Congress, CAC 2024

作者： He, Wenbin Mao, Jianxu Wang, Yaonan Li, Zhe Yan, Feng Liu, Kexin College of Electrical & Information Engineering National Engineering Research Center of Robot Visual Perception & Control Technology Hunan University Hunan China College of Control Science & Engineering State Key Laboratory of Industrial Control Technology Zhejiang University Zhejiang China

ISBN: (纸本)9798350368604

The deep convolution method based on MSDP signal imaging has been proven to be an effective means of monitoring the robot grinding process. This method has very high requirements on the quality of imaging and requires a lot of computing resources. This paper proposes an image self-contrastive learning network that can effectively extract fault information from low-pixel fuzzy images and achieve efficient and accurate condition monitoring. The network first calculates the correlation distance matrix between two identical modified symmetrized dot pattern (MSDP) images and uses the generated similarity labels to calculate the contrast loss to extract the embedded features of the image. Finally, the classification network is trained using the cross entropy loss to achieve the classification of fault images. The method was verified on a robotic grinding platform to significantly reduce the calculation time while maintaining the recognition accuracy, which provides reliable technical support for the real-time monitoring of the robotic grinding process. © 2024 IEEE.

关键词： Contrastive Learning fault diagnosis robotic grinding signal imaging

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Error-State Model Predictive control of Quadrotors on SE(3)∗

Error-State Model Predictive Control of Quadrotors on SE(3)∗

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Wang, Sifei Miao, Zhiqiang Lin, Qiong Lin, Jie Zeng, Jianxin Chen, Lin Wang, Yaonan Hunan University College of Electrical and Information Engineering The National Engineering Laboratory for Robot Visual Perception and Control Changsha410082 China

ISBN: (纸本)9798350327182

Trajectory tracking is a basic problem in quadrotor control. To achieve a better control effect, MPC is introduced in the control of quadrotors. In this paper, we introduce the error-state dynamic model of a quadrotor firstly. Then, we develop an MPC method via the Lie group of special euclidean group based on the error-state dynamic model of a quadrotor. The proposed method is established on a manifold, thus the smoothness of the quadrotor trackjectory can be guaranteed. Our scheme is developed in error-state, which means that we take the velocity of the target trajectory into consideration for the dynamic model building. Therefore the cost function of our proposed approach is convex while the traditional MPC method is not when tracking a nonlinear trajectory. At the end of this paper, we compare our proposed MPC method with the traditional MPC method in one hundred sets of simulations. In our proposed method, the errors of position and orientation converge faster than the errors in the traditional method. The simulation results show that our proposed method is superior to traditional MPC scheme while tracking a nonlinear trajectory with a random initial position and verity the correctness of our MPC method. © 2023 IEEE.

关键词： Model predictive control

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Dynamic Movement Primitives Based robot Skills Learning

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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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A lightweight intrusion detection method for intelligent substations 3

A lightweight intrusion detection method for intelligent sub...

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3rd International Conference on Electronic Information engineering and Data Processing, EIEDP 2024

作者： Zhang, Zidong Liu, Dongqi Liang, Haolan School of Electrical and Information Engineering Changsha University of Science and Technology Hunan410114 China National Engineering Research Center for Robot Visual Perception and Control Technology Hunan410012 China

ISBN: (纸本)9781510680531

Aiming at the current problem of lack of effective data and high service latency for intrusion detection in smart substations, this paper proposes a lightweight intrusion detection method for smart substations. Through the federated learning method and knowledge distillation method this paper trains a lightweight intrusion detection model based on LSTM. Experiments show that this paper's method has a large improvement in the accuracy and service delay on the NSL-KDD dataset. © 2024 SPIE.

关键词： Distillation

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