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Obstacle-circumventing adaptive control of a four-wheeled mobile robot subjected to motion uncertainties

Frontiers of Mechanical Engineering 2023年第3期18卷 123-143页

作者： Yiming YAN Shuting WANG Yuanlong XIE Hao WU Shiqi ZHENG Hu LI School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China

To achieve the collision-free trajectory tracking of the four-wheeled mobile robot(FMR),existing methods resolve the tracking control and obstacle avoidance *** the synergistic robustness and smooth navigation of mobile robots subjected to motion uncertainties in a dynamic environment using this non-cooperative processing method is *** address this challenge,this paper proposes an obstacle-circumventing adaptive control(OCAC)***,a novel anti-disturbance terminal slide mode control with adaptive gains is formulated,incorporating specified control laws for different *** formulation guarantees rapid convergence and simultaneous chattering *** introducing sub-target points,a new sub-target dynamic tracking regression obstacle avoidance strategy is presented to transfer the obstacle avoidance problem into a dynamic tracking one,thereby reducing the burden of local path searching while ensuring system stability during obstacle *** experiments demonstrate that the proposed OCAC method can strengthen the convergence and obstacle avoidance efficiency of the concerned FMR system.

关键词： four-wheeled mobile robot obstacle-circumventing adaptive control adaptive anti-disturbance terminal sliding mode control sub-target dynamic tracking regression obstacle avoidance

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A noise reduction method based on PSR-fastICA for spectrum-induced polarization data 2

A noise reduction method based on PSR-fastICA for spectrum-i...

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2nd International Conference on Electronic Information Technology, EIT 2023

作者： Cen, Wei Li, Zhihua School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (数字)9781510666627

ISBN: (纸本)9781510666610

Spectrum-induced polarization (SIP) is a widely used geophysical exploration approach, but it is prone to noise. To address this issue, this paper proposes a noise reduction method that combines phase space reconstruction (PSR) and fast independent component analysis (fastICA). The proposed approach enhances the signal-to-noise ratio of SIP data by effectively removing noise. Experimental results show that the PSR-fastICA method significantly reduces noise in SIP signals. © 2023 SPIE.

关键词： Signal to noise ratio

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A practical PID variable stiffness control and its enhancement for compliant force-tracking interactions with unknown environments

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Science China(Technological Sciences) 2023年第10期66卷 2882-2896页

作者： ZHANG Xin ZHOU Hao LIU JinGuo JU ZhaoJie LENG YuQuan YANG ChenGuang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China University of Chinese Academy of Sciences Beijing 100049China School of Computing University of PortsmouthPortsmouth PO13HEUK Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy EngineeringSouthern University of Science and TechnologyShenzhen 518055China Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and EngineeringSouth China University of TechnologyGuangzhou 510640China

Compliant interaction control is a key technology for robots performing contact-rich manipulation *** design of the compliant controller needs to consider the robot hardware because complex control algorithms may not be compatible with the hardware performance,especially for some industrial robots with low bandwidth *** paper focuses on effective and easy-to-use compliant control algorithms for position/velocity-controlled *** by human arm stiffness adaptation behavior,a novel variable target stiffness(NVTS)admittance control strategy is proposed for adaptive force tracking,in which a proportional integral derivative(PID)variable stiffness law is designed to update the stiffness coefficient of the admittance function by the force and position ***,its stability and force-tracking capability are theoretically *** addition,an impact compensator(Impc)is integrated into the NVTS controller to enhance its disturbance-suppression capability when the robot is subjected to strong vibration disturbances in complicated surface polishing *** proposed controllers are validated through four groups of experimental tests using different robots and the corresponding results demonstrate that they have high-accuracy tracking capability and strong adaptability in unknown environments.

关键词： compliant interaction control force tracking PID variable stiffness impact compensator unknown environments

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An Improved YOLOv5 Detection Algorithm with Pruning and OpenVINO Quantization

An Improved YOLOv5 Detection Algorithm with Pruning and Open...

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2023 China Automation Congress, CAC 2023

作者： Chen, Cheng Gan, Yahui Han, Zao Gao, Huan Li, Ang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education NanJing China Nanjing YingQi Intelligent Technology Co. Ltd. Intel Joint Research Institute on Intelligent Edge Computing NanJing China

ISBN: (纸本)9798350303759

In order to address the problem of current object detection models being too large to be deployed on robot controllers, this paper proposes improvements to YOLOv5 for real-time detection. The YOLOv5s model is pruned at the Batch Normalization (BN) layer, and further optimized using the OpenVINO tool for quantization. The results demonstrate that our improvements effectively improve the model's inference speed while maintaining its accuracy. Compared to the original YOLOv5 model, the pruned model achieves the same accuracy without degradation, with a 36.6% reduction in parameter count and a 35% reduction in weight storage file size. Furthermore, after optimization with OpenVINO, the final model achieves a FPS of 56. © 2023 IEEE.

关键词： Object detection

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Facial expression recognition under occlusion conditions based on multi-feature cross-attention

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Journal of intelligent and Fuzzy systems 2024年第4期46卷 9841-9856页

作者： Guo, Sheng Tan, Mian Cai, Shan Zhang, Zaijun Liang, Yihui Feng, Hongxi Zou, Xue Wang, Lin School of Data Science and Information Engineering Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang China School of Mathematics and Statistics Qiannan Normal University for Nationalities Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province Duyun China Zhongshan Institute University of Electronic Science and Technology of China Zhongshan China Guizhou Aerospace Tianma Electromechanical Technology Co LTD Zunyi China

Although facial expression recognition (FER) has a wide range of applications, it may be difficult to achieve under local occlusion conditions which may result in the loss of valuable expression features. This issue has motivated the present study, as a part of which an effective multi-feature cross-attention network (MFCA-Net) is proposed. The MFCA-Net consists of a two-branch network comprising a multi-feature convolution module and a local cross-attention module. Thus, it enables decomposition of facial features into multiple sub-features by the multi-feature convolution module to reduce the impact of local occlusion on facial expression feature extraction. In the next step, the local cross-attention module distinguishes between occluded and unoccluded sub-features and focuses on the latter to facilitate FER. When the MFCA-Net performance is evaluated by applying it to three public large-scale datasets (RAF-DB, FERPlus, and AffectNet), the experimental results confirm its good robustness. Further validation is performed on a real FER dataset with local occlusion of the face. © 2024 – IOS Press.

关键词： Convolution

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An Adaptive Padding Correlation Filter With Group Feature Fusion for Robust Visual Tracking

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1845-1860页

作者： Zihang Feng Liping Yan Yuanqing Xia Bo Xiao Key Laboratory of Intelligent Control and Decision of Complex Systems the School of AutomationBeijing Institute of TechnologyBeijing 100081China IEEE the School of Artificial Intelligence Beijing University of Posts and TelecommunicationsBeijing 100876China

In recent visual tracking research,correlation filter(CF)based trackers become popular because of their high speed and considerable *** methods mainly work on the extension of features and the solution of the boundary effect to learn a better correlation ***,the related studies are *** exploring the potential of trackers in these two aspects,a novel adaptive padding correlation filter(APCF)with feature group fusion is proposed for robust visual tracking in this paper based on the popular context-aware tracking *** the tracker,three feature groups are fused by use of the weighted sum of the normalized response maps,to alleviate the risk of drift caused by the extreme change of single ***,to improve the adaptive ability of padding for the filter training of different object shapes,the best padding is selected from the preset pool according to tracking precision over the whole video,where tracking precision is predicted according to the prediction model trained by use of the sequence features of the first several *** sequence features include three traditional features and eight newly constructed *** experiments demonstrate that the proposed tracker is superior to most state-of-the-art correlation filter based trackers and has a stable improvement compared to the basic trackers.

关键词： Adaptive padding context information correlation filter(CF) feature group fusion robust visual tracking

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Strong Co-Location Pattern Mining Incorporating Multi-Path and Distance Decay Effects 7

Strong Co-Location Pattern Mining Incorporating Multi-Path a...

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7th International Conference on Algorithms, computing and Artificial Intelligence, ACAI 2024

作者： He, Yonggui Yang, Peizhong Wang, Lizhen Chen, Hongmei Yunnan University School of Information Science and Engineering Kunming China Yunnan University Yunnan Key Laboratory of Intelligent Systems and Computing School of Information Science and Engineering Kunming China

ISBN: (纸本)9798331529314

Spatial co-location pattern mining (SCPM) is a sub-field of data mining, which aims to discover the subset of spatial features whose instances are frequently located in proximate areas. SCPM has broad prospects in many applications, such as ecology, public health, smart cities, etc. In recent years, improving and applying SCPM technology with the constraints of road networks has emerged as a prominent research focus. However, existing studies solely focus on the shortest path between instances when assessing the proximity relationships, neglecting other proximity paths, and thus may overlook co-location patterns with strong associations. To address this issue, this paper introduces a novel metric called Strong Proximity Score, which integrates both multi-path proximity and distance decay effects to measure the strength of proximity relationships. Additionally, the Minimum First Search (MFS) algorithm is presented, which utilizes the strategy of minimum instance pair search to accelerate the calculation of Strong Proximity Score. Extensive experiments conducted on real datasets of points of interest demonstrate the superiority of the method based on Strong Proximity Score over traditional SCPM methods and confirm the efficiency of MFS algorithm. © 2024 IEEE.

关键词： Smart city

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A modular four-modal soft grasping device

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Science China(Technological Sciences) 2022年第8期65卷 1845-1858页

作者： GAI LingJie ZONG XiaoFeng School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China

It is a key challenge for soft grasping devices to stably grasp unstructured objects with multi-size and multi-shape. The conventional single-function grippers have some limitations in grasping the above kinds of objects. This work proposes a modular four-modal soft grasping device(MFSGD), which consists of soft fingers, suction cups, soft wrapper, and other structures. It can perform a variety of grasping modes such as bending grasping mode, wrapping grasping mode, end liftingsucking mode, and side fixed-sucking mode. It may be one of the devices with the most grasping modes at present. Moreover, the device adopts a fully modular design with different structures connected by magnets. It is not only convenient to disassemble or assemble, so as to solve the mutual interference of different modal structures problem during grasping, but also simplifies the fabrication of the multi-modal grasping device. In addition, this work matches the suitable grasping modes for objects of different shapes and sizes, and obtains the relative characteristics of the MFSGD. The proposed device can improve the ability of the grasping robots, and is expected to play an important role in economic and industrial fields.

关键词： four-modal soft grasping device modular suction cups soft wrapper soft fingers

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A Fully Soft Bionic Grasping Device with the Properties of Segmental Bending Shape and Automatically Adjusting Grasping Range

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Journal of Bionic Engineering 2022年第5期19卷 1334-1348页

作者： Lingjie Gai Xiaofeng Zong School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China

In this paper,we propose a fully Soft Bionic Grasping Device(SBGD),which has advantages in automatically adjusting the grasping range,variable stiffness,and controllable bending *** device consists of soft gripper structures and a soft bionic bracket *** adopt the local thin-walled design in the soft gripper *** design improves the grippers’bending efficiency,and imitate human finger’s segmental bending *** addition,this work also proposes a pneumatic soft bionic bracket structure,which not only can fix grippers,but also can automatically adjust the grasping space by imitating the human adjacent fingers’opening and closing *** to the above advantages,the SBGD can grasp larger or smaller objects than the regular grasping ***,to grasp small objects reliably,we further present a new Pinching Grasping(PG)*** great performance of the fully SBGD is verified by *** work will promote innovative development of the soft bionic grasping robots,and greatly meet the applications of dexterous grasping multi-size and multi-shape objects.

关键词： Fully soft bionic grasping device Local thin-walled grippers Soft bionic bracket Adjust grasping range automatically Segmental bending shape New pinching grasping method

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A novel deep domain-adversarial method based on DRN-DATL for rolling bearing 43

A novel deep domain-adversarial method based on DRN-DATL for...

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43rd Chinese Control Conference, CCC 2024

作者： Li, Zhuorui Wang, Xiaodong Ma, Bao Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650500 China Yunnan University Yunnan Key Laboratory of Intelligent Systems and Computing Kunming650500 China

ISBN: (纸本)9789887581581

In recent years, a variety of rolling bearing fault diagnosis methods based on deep learning has become an emerging research orientation. However, there is still a gap between the existing diagnostic model and the practical application, i.e., 1) due to the variability of working conditions, the domain shift problem between source domain and the target domain have led to the obvious degradation of the diagnostic performance. 2) It is time-consuming and expensive to label a mass of monitoring data in practical situation. To address this problem, a domain-adversarial transfer learning method based on deep residual network (DRN-DATL) for rolling bearing fault diagnosis is proposed. Firstly, DRN is designed to extract features from raw vibration signal, which can avoid gradient problems. Then, the APReLU activation function is adopted to improved diagnostic accuracy under different working conditions. Meanwhile, domain-adversarial training is utilized to minimize distribution differences between source domain and target domain. Finally, seven comparison methods are selected for systematic analysis, and the results show that the proposed method can effectively improve the overall performance of the diagnosis model, which has achieved higher classification accuracy. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Adversarial machine learning

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