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5th IEEE Advanced Information Management, Communicates, Electronic and Automation control Conference, IMCEC 2022

作者： Qingxian, Liu Jianxu, Mao Junfei, Yi Ziming, Tao Junlong, Yu College of Electrical and Information Engineering Hunan University Changsha China National Engineering Research Center for Robot Vision Perception and Control Technology Changsha China

ISBN: (纸本)9781665479677

The working state of fasteners is closely related to the safe and stable operation of the power grid. However, the performance of the existing fastener defect detection models is not enough to meet the requirements, because the size of object is small, the environment is complex, the sample size is unbalanced and so on. Therefore, we design a simple but effective feature fusion method, called Double Context Information Enhancement Module. The model can fully learn the features of fasteners by expanding the receptive field of the feature map during the construction of the feature pyramid, and the feature expression ability of fasteners can be enhanced by learning the features of adjacent layers after the construction of the feature pyramid. Through experiments, we proved that DCEM can improve about 8.8AP compared with the original model, and at the same time, the effectiveness and advancement of DCEM are proved by comparing with SOTA. © 2022 IEEE.

关键词： Defects

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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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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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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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Admittance Based robot Force control Framework for Server Board Assembly 25

Admittance Based Robot Force Control Framework for Server Bo...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Ma, Yunlong Wang, Yaonan Jiang, Yiming Zhou, Xianen Zhu, Ge Zhu, Qing Institute of Artificial Intelligence University of Science and Technology Beijing Beijing China Xiangjiang Laboratory Hunan China College of Electrical and Information Engineering Hunan University Changsha China School of Robotics Hunan University Changsha China National Engineering Research Center for Robot Vision Perception and Control Technology Hunan University Changsha China ZTE Corporation Shenzhen China

In server board assembly tasks, the effect of vision-based robot assembly schemes is not ideal due to the small installation gap and the blocking of vision. Adding force sensors and force controllers can be a good solution to the above problems and increase the flexibility in the assembly process. In this paper, we propose a force control strategy applied to a server board assembly task. The method is divided into two main parts. In the first part, the zero offset of the force sensor and the load gravity are calibrated and compensated, so that the external force on the load is accurately obtained. In the second part, the admittance controller is designed to achieve compliant behavior between the robot and the environment. Finally, the experimental verification of the board insertion is carried out on the experimental platform. Experimental results verify the effectiveness and practicability of the proposed method. © 2024 IEEE.

关键词： controllers

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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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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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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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Electromagnetism-Like Mechanism Algorithm with New Charge Formula for Optimization

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Journal of Donghua University(English Edition) 2021年第3期38卷 231-239页

作者： YIN Feng KANG Yongliang ZHANG Dongbo QIU Jie College of Automation and Electronic Information Xiangtan University Xiangtan 411105 China National Engineering Laboratory of Robot Vision Perception and Control Technology Xiangtan University Xiangtan 411105 China

The electromagnetism-like(EM)algorithm is a meta-heuristic optimization algorithm,which uses a novel searching mechanism called attraction-repulsion between charged *** is worth pointing out that there are two potential problems in the calculation of particle charge by the original EM *** of the problems is that the information utilization rate of the population is not high,and the other problem is the decline of population diversity when the population size is much greater than the dimension of the *** contrast,it is more fully to exploit the useful search information based on the proposed new quadratic formula for charge calculation in this ***,the population size was introduced as a new multiplier term to improve the population *** the end,numerical experiments were used to verify the performance of the proposed method,including a comparison with the original EM algorithm and other well-known methods such as artificial bee colony(ABC),and particle swarm optimization(PSO).The results showed the effectiveness of the proposed algorithm.

关键词： electromagnetism-like(EM)mechanism stochastic search method constrained optimization global optimization attraction-repulsion

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