检索结果-内蒙古大学图书馆

Chinese Automation Congress (CAC)

作者： Jiahao Sun Xin Ma Yibin Li Center for Robotics School of Control Science and Engineering Shandong University Engineering Research Center of Intelligent Unmanned System Ministry of Education Jinan China

Estimating the 6D object pose from a singular RGB image is a fundamental task in the field of computer vision. Recent studies have demonstrated that keypoint-based methods exhibit remarkable efficacy. Such methodologies initially identify keypoints and subsequently deduce the object”s pose by addressing a Perspective-n-Point (PnP) problem. Nonetheless., the prevalent approach of directly regressing the 2D coordinates of keypoints renders these methods sensitive to occlusions. Instead., we inaugurate a coarse-to-fine keypoint localization network (C2FNet)., where we utilize the predicted keypoint offsets from the first stage as input to deformable convolutional networks (DCN) in the second stage., to further capture geometric features and enhance spatial relationships between keypoints., thus outputting accurate and robust keypoint coordinates. Experiments indicate that the proposed approach surpasses existing advanced methods in terms of performance on the LINEMOD and Occlusion LINEMOD datasets.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Semantic-guided modeling of spatial relation and object co-occurrence for indoor scene recognition

arXiv

引用

arXiv 2023年

作者： Song, Chuanxin Wu, Hanbo Ma, Xin Center for Robotics School of Control Science and Engineering Shandong University China Engineering Research Center of Intelligent Unmanned System Ministry of Education China

Exploring the semantic context in scene images is essential for indoor scene recognition. However, due to the diverse intra-class spatial layouts and the coexisting inter-class objects, modeling contextual relationships to adapt various image characteristics is a great challenge. Existing contextual modeling methods for scene recognition exhibit two limitations: 1) They typically model only one type of spatial relationship (order or metric) among objects within scenes, with limited exploration of diverse spatial layouts. 2) They often overlook the differences in coexisting objects across different scenes, suppressing scene recognition performance. To overcome these limitations, we propose SpaCoNet, which simultaneously models Spatial relation and Co-occurrence of objects guided by semantic segmentation. Firstly, the Semantic Spatial Relation Module (SSRM) is constructed to model scene spatial features. With the help of semantic segmentation, this module decouples spatial information from the scene image and thoroughly explores all spatial relationships among objects in an implicit manner, thereby obtaining semantic-based spatial features. Secondly, both spatial features from the SSRM and deep features from the Image Feature Extraction Module are allocated to each object, so as to distinguish the coexisting object across different scenes. Finally, utilizing the discriminative features above, we design a Global-Local Dependency Module to explore the long-range co-occurrence among objects, and further generate a semantic-guided feature representation for indoor scene recognition. Experimental results on three widely used scene datasets demonstrate the effectiveness and generality of the proposed method. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Neural Network-Based Terminal Sliding Mode controller Design for Manipulator systems 1

引用

UNIfied Conference of International Workshop on Defence Applications of Multi-Agent systems, DAMAS 2023, International Conference on Maintenance engineering, IncoME-V 2023, International conference on the Efficiency and Performance engineering Network, TEPEN 2023

作者： Qu, Lufeng Fan, Qiming Kang, Yang Yang, Jun Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China School of Intelligent Manufacturing Tianjin Sino-German University of Applied Technology Tianjin300350 China School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9783031494130

ISBN: (纸本)9783031494123

In the context of nonlinear and uncertain manipulator systems, achieving fast and accurate desired trajectories for each joint of the manipulator is crucial. Our study aims to improve current control methods by combining sliding mode control and neural network techniques. Specifically, we leverage the neural networks’ approximation capabilities to estimate both the modeling error and external disturbance in our research. These estimates are then integrated into the synovial control as additional gains. This approach allows for the sliding mode controller’s switch gain to adapt to changing modeling error and external disturbance, thereby avoiding the vibration production typically associated with traditional sliding mode controllers. It can be observed from the simulation results that the combination of the proposed nonsingular terminal sliding mode controller and neural network achieves fast and precise tracking of desired trajectories. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Sliding mode control

来源：评论

学校读者我要写书评

暂无评论

Bearing-Based Target Entrapping control of Multiple Uncertain Agents With Arbitrary Maneuvers

引用

IFAC-PapersOnLine 2023年第2期56卷 8821-8826页

作者： Haifan Su Ziwen Yang Shanying Zhu Cailian Chen Wenbin Yu Department of Automation Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

This paper is concerned with bearing-based cooperative target entrapping control of multiple uncertain agents with arbitrary maneuvers including shape deformation, rotations, scalings, etc. A leader-follower structure is used, where the leaders move with the predesigned trajectories, and the followers are steered by an estimation-based control method, integrating a distance estimator using bearing measurements and a stress matrix-based formation controller. The signum functions are used to compensate for the uncertainties so that the agents’ accelerations can be piecewise continuous and bounded to track the desired dynamics. With proper design of the leaders’ trajectories and a geometric configuration, an affine matrix is determined so that the inter-agent relative bearings can be persistently exciting since the bearing rates are related to different weighted combinations of the affine matrix vectors. The asymptotic convergence of the estimation and control error is proved using Filipov properties and cascaded system theories. A sufficient condition for inter-agent collision avoidance is also proposed. Finally, simulation results are given to validate the effectiveness of the method.

关键词： Target entrapping control bearing measurement persistent excitation uncertainty

来源：评论

学校读者我要写书评

暂无评论

Spatial-Temporal-Rule-based Traffic Movement Status Interpretation at Intersections *

Spatial-Temporal-Rule-based Traffic Movement Status Interpre...

引用

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

作者： Zhuang, Hanyang Gao, Liyang Qian, Yeqiang Wang, Chunxiang Yang, Ming University of Michigan Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9798350327182

Traffic light is the most significant component of road transportation. Traffic lights control the traffic movement at intersections by allowing the movement of some lanes and forbidding that of the others to ensure safety and efficiency. It is important for intelligent vehicles to understand the meaning of traffic lights. Conventional research works on traffic light detection and tracking consider each light independently, so the occlusion of some lights may mislead the decision of the vehicle. Since all traffic lights at an intersection work together, it is more essential to understand the traffic movement status controlled by the traffic lights rather than the perception of a single light. Therefore, this paper proposes a spatial-temporal-rule-based framework to interpret the current traffic movement status and predict the next status. The spatial information, including position and class, is obtained by traffic light detection. The temporal information is perceived by the proposed topologic-feature-based tracking method. The rule information is recognized by combination of spatial and temporal information. A dual-view camera system consisting of a telephoto camera and a wide-angle camera is adopted to ensure long perception distance and wide coverage simultaneously. The successful tracking of traffic lights from 200 m to 10 m away provides enough data to recognize the phase-change rule, which leads to correct interpretation and prediction. A customized dataset was collected, and experiments were conducted to illustrate the capability of the proposed method. © 2023 IEEE.

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

Landing Area Prediction in Complex Terrains for Walking-assisted Lower-limb Exoskeleton Robot

Landing Area Prediction in Complex Terrains for Walking-assi...

引用

2023 International Conference on Biomimetic Intelligence and Robotics

作者： Liu, Yuexun Liu, Du-Xin Ma, Yue Guo, Sheng Wu, Xinyu Robotics Research Center School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing100044 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

With the expansion of application scenarios, the walking-assisted lower-limb exoskeleton robot urgently needs to improve its walking ability in complex terrains. However, due to the lack of environmental understanding ability and decision-making ability, the exoskeleton can not meet the need of people with lower-limb disability in complex terrains. To improve the walking abillity, this paper proposes a method of predicting the landing area in complex terrains for walking-assisted lower-limb exoskeleton robot. Multiple sensors were used to obtain the terrain information, step length, and stride length of human walking, and a multi-type input convolutional network was built to establish the mapping relationship to learn the decision-making mechanism of human standing in a complex environment. The result shows that the established network effectively predicts the landing area. Under the condition of full training, the predicted position deviation of the landing area is controlled within 6%, and the prediction rationality of the landing area can reach 90%. © 2023 The Authors. Published by Elsevier B.V.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Explicit Predictive control of Forward DC-DC Converter Based on an Input-Mapping Method

Explicit Predictive Control of Forward DC-DC Converter Based...

引用

第43届中国控制会议

作者： Xiang Gu Dewei Li Aoyun Ma Yaru Yu Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In the practical application of model predictive control in power electronics, both online computational burden and model accuracy are crucial. This paper presents an explicit model predictive control method based on input-mapping *** address the issue of parameter drift in the forward DC-DC converter system, the input-mapping method is introduced to compensate for model deviations using historical data. Firstly, the average model of the forward DC-DC converter system is introduced. For the control objective of voltage tracking, an explicit predictive control using the incremental model is ***, input-mapping method is integrated with explicit predictive control. During offline computation, analytical forms of the input-mapping combination coefficients and the optimal solution function of explicit model predictive control are *** computation of combination coefficients is conducted to obtain the optimal solution rapidly. The effectiveness of the proposed method is verified through simulations in MATLAB.

关键词： Forward DC-DC converter explicit model predictive control input-mapping method

来源：评论

学校读者我要写书评

暂无评论

Trajectory Optimization and control Method Based on Multistage Nonlinear Model Predictive control 4

Trajectory Optimization and Control Method Based on Multista...

引用

4th International Seminar on Artificial Intelligence, Networking and Information Technology, AINIT 2023

作者： Zheng, Qingchun Peng, Zhi Zhu, Peihao Zhai, Ran Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin China School of Mechanical Engineering Tianjin University of Technology Tianjin China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin China

ISBN: (纸本)9798350314526

To improve the trajectory optimization efficiency of robot manipulators, this paper proposes a novel approach for trajectory optimization and control of manipulators based on multistage nonlinear model predictive control (msNLMPC). This approach is realized by using a neural state space model as the prediction model of nonlinear model predictive control (NLMPC). The simulation results show that the actual trajectory of the manipulator in our proposed scheme coincides with the desired trajectory. The manipulator achieves the control task of following the optimal trajectory. Our proposed method improves the trajectory optimization efficiency of the robot manipulator. © 2023 IEEE.

关键词： Model predictive control

来源：评论

学校读者我要写书评

暂无评论

Research on Identification Strategy of Fault-Sensitive Frequency for Planetary Gearboxes

Research on Identification Strategy of Fault-Sensitive Frequ...

引用

TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Xie, Ruitong Zhang, Mian Chen, Jiwei Zhu, Songsong Wang, Zhiyuan Zhao, Mengxiong Xiang, Hongbiao Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechanical System Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Binshuixidao 391 Xiqing District Tianjin300384 China State Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan430072 China

ISBN: (纸本)9783031694820

Planetary gearboxes find extensive application in wind power generation, aerospace, industrial production and other fields. Harsh operational conditions and prolonged periods of continuous work often lead to various gear damages. Therefore, it is important to continuously monitor the health status of planetary gearboxes. However, the fault-sensitive frequencies of planetary gearboxes used in the existing signal models and fault diagnosis indicators are calculated theoretically or searched artificially. In response to this, this paper proposes a strategy for identifying fault-sensitive frequencies in planetary gearboxes intelligently by combining spectral amplitude analysis with three models: Random Forest (RF), Support Vector Machine (SVM) and Deep Neural Network (DNN). Experiments are carried out to verify the effectiveness and superiority of the proposed strategy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

An Order Demodulation Analysis Method for Planetary Gearboxes

An Order Demodulation Analysis Method for Planetary Gearboxe...

引用

TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Chen, Jiwei Xie, Ruitong Zhu, Songsong Zhao, Mengxiong Wang, Zhiyuan Zhang, Mian Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechanical System Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Binshuixidao 391 Xiqing District Tianjin300384 China State Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan430072 China

ISBN: (纸本)9783031694820

In addressing challenges such as the speed change of planetary gearbox (PG) during operation and the complexity in extracting fault features, an order demodulation analysis method based on order tracking (OT) and variational mode decomposition (VMD) is proposed. Non-stationary time domain signals are transformed into relatively stable angular domain signals through angular resampling. The intrinsic mode function (IMF) is obtained by demodulation of the angular multi-component signal using the VMD method. The instantaneous order of a proper IMF is calculated via Hilbert Transform. The sensitive single component is selected by matching the meshing order and the central order of the instantaneous order. Finally, the amplitude of the characteristic order components extracted from the instantaneous order spectrum was used as features and Support Vector Machine (SVM) was employed for the classification of four different conditions in the sun gear. Comparing the results of the proposed method with Deep Neural Networks (DNN) and Convolutional Neural Networks (CNN), the experimental results demonstrate the effectiveness of the proposed method in diagnosing PGs under non-stationary conditions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Epicyclic gears

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：