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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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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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Velocity-free Formation control for Quadrotors Using High-order Sliding Mode Differentiator

Velocity-free Formation Control for Quadrotors Using High-or...

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

作者： Lin, Qiong Miao, Zhiqiang Wang, Yaonan Hunan University College of Electrical and Information Engineering Changsha410082 China National Engineering Research Center for Robot Visual Perception and Control Changsha China

ISBN: (纸本)9798350327182

This paper deals with the problem of achieving formation control for underactuated multiple quadrotors without velocity measurements by employing the higher-order sliding mode (HOSM) differentiator. The primary objective of this work is to attain a coordinated formation behavior among the quadrotor group. In this paper, the dynamics of each quadrotor are transformed into a new form, wherein the attitude is described using rotation matrices. Subsequently, an intermediate guide is designed using the HOSM differentiator, taking into account the desired relative positions between the quadrotors and their actual positions. Next, the actual control thrusts and torques for each quadrotor are designed and solved by the intermediate guide. Finally, rigorous theoretical analysis and multiple simulations are performed to ensure that the multiple quadrotors converge asymptotically and accurately to the desired formation shape. © 2023 IEEE.

关键词： Sliding mode control

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Double-layer Descriptors and High-dimensional Search Mechanisms for Partial Point Cloud Registration

Double-layer Descriptors and High-dimensional Search Mechani...

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2023 China Automation Congress, CAC 2023

作者： Wang, Zhiyu Fang, Qiu Wang, Yaonan Lu, Hong Ye, Jun National Engineering Research Center for Robot Visual Perception and Control Technology School of Electrical and Information Engineering Hunan University Hunan Changsha410082 China

ISBN: (纸本)9798350303759

Partial point cloud registration is an essential preprocessing technique to generate complete 3D shapes that aim to transform partial scans into a common coordinate system. Existing methods that utilize geometric alignment rarely combine local and global information, which results in many incorrect correspondences. In the paper, a two-layer descriptor and a high-dimension searching approach (DDHSM) are utilized to extract and select the correct correspondences. Firstly, in the first layer, the Fast Point Feature Histogram (FPFH) is used to describe the feature of every point with high-dimension information based on its robustness and fastness. Then a high-dimensional search is considered to extract the initial corresponding set. In the second layer, global information is introduced to find the correct correspondences. For each point pair in the initial corresponding set, the normal angles are compared for all remaining points that satisfy the distance requirement. Finally, the singular value decomposition (SVD) method is implemented to compute the rigid transformation based on the updated corresponding set. Experimental results and comparisons with state-of-the-art methods demonstrate the effectiveness and feasibility of our approach. © 2023 IEEE.

关键词： Graphic methods

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Robust Stereo VIO Based on an Equivariant Filter for Complex Lighting Environments

Robust Stereo VIO Based on an Equivariant Filter for Complex...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Chen, Zhenhang Miao, Zhiqiang Wang, Chuancheng Wang, Yaonan College of Electrical and Information Engineering The National Engineering Laboratory for Robot Visual Perception and Control Hunan University Changsha410082 China

ISBN: (纸本)9781665481090

visual Inertial Odometry(VIO) is widely used in various fields. When lighting conditions change dramatically, the visual front-end is affected, resulting in performance degradation and even failure in some extreme scenarios. In this paper, a stereo VIO based on an equivariant filter(EqF) for complex lighting environments is proposed. We propose a new adaptive gamma correction method, which can effectively improve the quality of image sequence and ensure the real-time performance of the algorithm because of the image selection processing strategy. Our VIO uses a robust stereo visual front-end and a state-of-the-art equivariant filter at the back-end. Experiments showed that the system has higher accuracy and robustness than another EqF-based VIO algorithm(EqF-VIO), and can work in complex and extreme lighting environments. © 2022 IEEE.

关键词： Image enhancement

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Geometric-based Bimodal control for Hybrid Aerial/Ground Vehicles

Geometric-based Bimodal Control for Hybrid Aerial/Ground Veh...

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2024 IEEE International Conference on Real-Time Computing and robotics, RCAR 2024

作者： Tang, Haoming Miao, Zhiqiang Wang, Haoyu Chen, Yizong Zhang, Hui Wang, Yaonan Hunan University College of Electrical and Information Engineering Changsha410082 China National Engineering Research Center for Robot Visual Perception and Control Changsha China School of Robotics Hunan University Changsha410082 China

ISBN: (纸本)9798350372601

Hybrid ground/aerial vehicles, capable of adapting to both terrestrial and aerial environments simultaneously, can accomplish more complex tasks, holding promising applications across various domains. Furthermore, designing a highly real-time multi-modal controller to adapt to environmental and modal changes, is currently a critical issue to be addressed. Based on this requirement, a geometric-based bimodal control structure is proposed in this study. We initially design the aerial controller in the Lie algebra space, based on a geometric attitude controller. Moreover, inspired by the characteristics of ground locomotion, we modify the aerial controller to satisfy the constraints of this mode. Through this approach, we can simplify the design process of the ground controller. Both controllers feature a similar and simpler structure, meet real-time control requirements, and allow them to use the same parameters. Ultimately, the proposed method's efficacy and performance are validated through ROS-Gazebo simulation environment. © 2024 IEEE.

关键词： Antenna grounds

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Intelligent monitoring method of bearings based on PCA-SOM 4

Intelligent monitoring method of bearings based on PCA-SOM

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4th International Conference on Testing Technology and Automation engineering, TTAE 2024

作者： Xiao, Xianghui Dai, Yanting Yin, Baixin Yuan, Xiaofang College of Automation Foshan University Guangdong Foshan520000 China National Engineering Laboratory of Robot Vision Perception and Control Technology Hunan Changsha410082 China

ISBN: (数字)9781510686656

ISBN: (纸本)9781510686649

To address the issues of excessive maintenance and untimely maintenance of bearings, this paper proposes a performance evaluation method for bearing condition monitoring based on the combination of Principal Component Analysis (PCA) and Self-Organizing Map (SOM) networks. This method utilizes PCA to reduce the dimensionality of dual-domain features and conducts clustering analysis using the SOM network, constructing a minimal quantization error as a degradation indicator to assess the bearing degradation state. This is an unsupervised approach that does not require the setting of training labels for the network. Experiments were conducted on the IMS dataset, and the results indicate that this method can effectively identify early bearing faults and reduce reliance on human expertise, thereby enhancing both overall efficiency and the intelligence level of assessments, ultimately achieving intelligent bearing fault recognition. © 2024 SPIE.

关键词： Conformal mapping

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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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RGB-Based Category-Level Object Pose Estimation via Depth Recovery and Adaptive Refinement

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IEEE robotics and Automation Letters 2025年第6期10卷 5377-5384页

作者： Yang, Hui Sun, Wei Liu, Jian Zheng, Jin Zeng, Zhiwen Mian, Ajmal Hunan University National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering Changsha410082 China Hunan University State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Changsha410082 China Central South University School of Architecture and Art Changsha410082 China University of Western Australia Department of Computer Science and Software Engineering CrawleyWA6009 Australia

Category-level pose estimation methods have received widespread attention as they can be generalized to intra-class unseen objects. Although RGB-D-based category-level methods have made significant progress, reliance on depth image limits practical application. RGB-based methods offer a more practical and cost-effective solution. However, current RGB-based methods struggle with object geometry perception, leading to inaccurate pose estimation. We propose depth recovery and adaptive refinement for category-level object pose estimation from a single RGB image. We leverage DINOv2 to reconstruct the coarse scene-level depth from the input RGB image and propose an adaptive refinement network based on an encoder-decoder architecture to dynamically improve the predicted coarse depth and reduce its gap from the ground truth. We introduce a 2D–3D consistency loss to ensure correspondence between the point cloud obtained from depth projection and the objects in the 2D image. This consistency supervision enables the model to maintain alignment between the depth image and the point cloud. Finally, we extract features from the refined point cloud and feed them into two confidence-aware rotation regression branches and a translation and size prediction residual branch for end-to-end training. Decoupling the rotation matrix provides a more direct representation, which facilitates parameter optimization and gradient propagation. Extensive experiments on the REAL275 and CAMERA25 datasets demonstrate the superior performance of our method. Real-world estimation and robotic grasping experiments demonstrate our model robustness to occlusion, clutter environments, and low-textured objects. Our code and robotic grasping video are available at DA-Pose. © 2016 IEEE.

关键词： Depth perception

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An Intelligent Route Recommendation Method for Smart Internet-Connected Electric Vehicles Under the Coupling of Traffic and Electricity 42

An Intelligent Route Recommendation Method for Smart Interne...

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42nd Chinese control Conference, CCC 2023

作者： Xie, Jinhuan Liu, Dongqi Yang, Zhenwu School of Electrical and Information Engineering Changsha University of Science and Technology Hunan 410114 China National Engineering Research Center for Robot Visual Perception and Control Technology Hunan 410012 China

ISBN: (纸本)9789887581543

Aiming at the charging and navigation strategy of electric vehicles in the road-electricity coupling scenario, this paper proposes a hybrid planning travel scheme based on the pre-charging and charging warning model based on the road traffic congestion predicted by the big data of the Internet of Vehicles. This model integrally balances the interests of users and power grid in the coupled road-electric network, and solves the optimal path scheme under different travel scenarios based on collaborative filtering algorithm and user feedback, considering the influence of vehicle departure time and remaining power in short time scale. It is experimentally demonstrated that the proposed route hybrid recommendation model has better planning effect compared with the single travel model. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Roads and streets

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