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第42届中国控制会议

作者： JinhuanXie Dongqi Liu ZhenwuYang School of Electrical and Information Engineering Changsha University of Science and Technology National Engineering Research Center for Robot Visual Perception and Control Technology

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 *** 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 *** is experimentally demonstrated that the proposed route hybrid recommendation model has better planning effect compared with the single travel model.

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A Mobile robotic System for Data center Thermal Environment Measurement and Reconstruction

A Mobile Robotic System for Data Center Thermal Environment ...

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Chinese Automation Congress (CAC)

作者： Ronghan Qin Qiu Fang Yaonan Wang National Engineering Laboratory for Robot Visual Perception and Control Technology Hunan University Changsha China

ISBN: (纸本)9781665426480

Data centers are the key infrastructure for information services. The monitoring of the thermal environment of the data center computer room is an important work for its safe operation. This paper proposed a mobile robotic system for data center thermal environment measurement, which can freely sample the temperature and humidity data around the facilities within the computer room. On one hand, measuring the temperature and humidity in a mobile way can obtain far more environmental data than fixed-point sensors. On the other hand, the mobile robot can be used instead of manual inspection. In addition, a temperature field reconstruction method is provided based on the sampled temperature data. Theoretically, the temperature of locations that have not been measured can be evaluated by interpolating sample temperature around them. The reconstruction of the temperature field can present the variation of the temperature more clearly and help find the hot spots or locations with low cooling efficiency during the operation. Lastly, experiments are carried out to study the measurement error of the mobile robotic system and an error correction method is proposed. After that, the relationship between the temperature reconstruction error and the layout of sampling points is investigated.

关键词： Temperature measurement Temperature sensors Temperature distribution Data centers Interpolation robot kinematics Reconstruction algorithms

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Towards Consistent Object Detection via LiDAR-Camera Synergy

Towards Consistent Object Detection via LiDAR-Camera Synergy

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Luo, Kai Wu, Hao Yi, Kefu Yang, Kailun Hao, Wei Hu, Rongdong College of Automotive and Mechanical Engineering Changsha University of Science and Technology China School of Traffic and Transportation Engineering Changsha University of Science and Technology China School of Robotics Hunan University China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University China Changsha Intelligent Driving Institute China

ISBN: (纸本)9781665410205

As human-machine interaction continues to evolve, the capacity for environmental perception is becoming increasingly crucial. Integrating the two most common types of sensory data, images, and point clouds, can enhance detection accuracy. Currently, there is no existing model capable of detecting an object's position in both point clouds and images while also determining their corresponding relationship. This information is invaluable for human-machine interactions, offering new possibilities for their enhancement. In light of this, this paper introduces an end-to-end Consistency Object Detection (COD) algorithm framework that requires only a single forward inference to simultaneously obtain an object's position in both point clouds and images and establish their correlation. Furthermore, to assess the accuracy of the object correlation between point clouds and images, this paper proposes a new evaluation metric, Consistency Precision (CP). To verify the effectiveness of the proposed framework, an extensive set of experiments has been conducted on the KITTI and DAIR-V2X datasets. The study also explored how the proposed consistency detection method performs on images when the calibration parameters between images and point clouds are disturbed, compared to existing post-processing methods. The experimental results demonstrate that the proposed method exhibits ex-cellent detection performance and robustness, achieving end-to-end consistency detection. The source code will be made publicly available at https://***/xifen523/COD. © 2024 IEEE.

关键词： Object detection

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A Muti-stage Selection Filter Based on Wavelet Packet and 2DCNN for Fault Diagnosis of Rotating Machinery 42

A Muti-stage Selection Filter Based on Wavelet Packet and 2D...

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42nd Chinese control Conference, CCC 2023

作者： He, Wenbin Mao, Jianxu Liu, Li Li, Zhe Yang, Miao Wang, Yaonan College of Electrical and Information Engineering Hunan University Changsha410082 China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410082 China State Grid Hunan Electric Power Company Limited Research Institute Changsha410007 China

ISBN: (纸本)9789887581543

Fault information of rotating machinery is often drowned in strong noise signals, so it is crucial to accurately identify faults from high-intensity noise signals. In this article, an end-to-end fault diagnosis model is developed, which consists of a multi-stage selection filter based on wavelet packet and 2D-CNN. First, the original measured mechanical signals were processed by the three-level wavelet packet decomposition to obtain eight sub-bands with coefficient matrices. Second, the signal is reconstructed using different numbers of sub-bands, where the number is increased by one at a time to obtain eight different multi-stage reconstructed signals. Third, the reconstructed signals are reorganized into 2D signal maps;and a parallel training network is constructed using signal maps and 2D-CNN to achieve fault classification. Then, guided by the training results, eight parallel classification results are compared, so as to train the best fault diagnosis model. Finally, the simulation experiment based on a bearing data set illustrates the proposed multi-stage selection filter is effective and feasible in application. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Failure analysis

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Motion Planning for Mobile robots with Temporal Logic Specifications

Motion Planning for Mobile Robots with Temporal Logic Specif...

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International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Jianxin Zeng Yaonan Wang Zhiqiang Miao Sifei Wang College of Electrical and Information Engineering and the National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha China

In this paper, we propose a motion planning method for mobile robots in order to satisfy task requirements specified in linear temporal logic (LTL). The proposed method follows the traditional hierarchical planning workflow, including path planning and trajectory planning. Firstly, we propose a path planning method based on rapidly exploring random trees (RRT*) and Dubins curve. The tree derived from RRT* is expanded with the help of Buchi automaton converted by an LTL formula. The proposed method can automatically adjust the iterations of sampling according to the scale of Buchi automata. Then, we formulate an optimization problem for the generation of trajectory. We use Bezier curve to express the trajectory and use differential flatness of mobile robots to simplify the optimization problem. Finally, we validate the practicality of our method through simulations and real-world experiments.

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A Graph Reconstruction by Dynamic Signal Coefficient for Fault Classification

arXiv

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arXiv 2023年

作者： He, Wenbin Mao, Jianxu Wang, Yaonan Li, Zhe Fang, Qiu Wu, Haotian The College of Electrical and Information Engineering The National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410082 China

To improve the performance in identifying the faults under strong noise for rotating machinery, this paper presents a dynamic feature reconstruction signal graph method, which plays the key role of the proposed end-to-end fault diagnosis model. Specifically, the original mechanical signal is first decomposed by wavelet packet decomposition (WPD) to obtain multiple sub-bands including coefficient matrix. Then, with originally defined two feature extraction factors MDD and DDD, a dynamic feature selection method based on L2 energy norm (DFSL) is proposed, which can dynamically select the feature coefficient matrix of WPD based on the difference in the distribution of norm energy, enabling each sub-signal to take adaptive signal reconstruction. Next the coefficient matrices of the optimal feature sub-bands are reconstructed and reorganized to obtain the feature signal graphs. Finally, deep features are extracted from the feature signal graphs by 2D-Convolutional neural network (2D-CNN). Experimental results on a public data platform of a bearing and our laboratory platform of robot grinding show that this method is better than the existing methods under different noise intensities. Copyright © 2023, The Authors. All rights reserved.

关键词： Feature extraction

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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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Chinese Automation Congress (CAC)

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

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.

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Safety-Critical control for Underwater Vehicles with Model Uncertainties and External Disturbances

Safety-Critical Control for Underwater Vehicles with Model U...

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International Conference on control, Automation, robotics and Vision (ICARCV)

作者： Yizong Chen Zhiqiang Miao Weiwei Zhan Yaonan Wang College of Electrical and Information Engineering Hunan University Changsha China National Engineering Research Center of Robot Visual Perception and Control Technology Changsha China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

Safety is a crucial issue for underwater vehicles, which may be affected by narrow terrain and multiple obstacles. In addition, the model of the underwater vehicles are uncertain and susceptible to external disturbances such as water flow. This article utilizes model predictive control (MPC) and incremental nonlinear dynamic inversion (INDI) to design a robust control scheme for underwater vehicles. The position loop controller employs MPC to generate the required speed commands for the velocity loop controller. The velocity loop is designed with an INDI control scheme incorporating a second-order low-pass filter, effectively mitigating model uncertainties and external disturbances on the vehicles. Based on exponential control barrier functions (ECBFs), the input constraint and obstacle avoidance problems of underwater vehicles are solved. The results indicate that the proposed control scheme not only exhibits robustness but also effectively ensures safe obstacle avoidance.

关键词： Uncertainty Three-dimensional displays Trajectory tracking Numerical simulation Robustness Safety Numerical models Collision avoidance Vehicle dynamics Underwater vehicles

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P2U-SLAM: A Monocular Wide-FoV SLAM System Based on Point Uncertainty and Pose Uncertainty

arXiv

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arXiv 2024年

作者： Zhang, Yufan Yang, Kailun Wang, Ze Wang, Kaiwei The State Key Laboratory of Extreme Photonics and Instrumentation Zhejiang University Hangzhou310027 China The School of Robotics The National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410012 China The National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410082 China

This paper presents P2U-SLAM, a visual Simultaneous Localization And Mapping (SLAM) system with a wide Field of View (FoV) camera, which utilizes pose uncertainty and point uncertainty. While the wide FoV enables considerable repetitive observations of historical map points for matching cross-view features, the data properties of the historical map points and the poses of historical keyframes have changed during the optimization process. The neglect of data property changes triggers the absence of a partial information matrix in optimization and leads to the risk of long-term positioning performance degradation. The purpose of our research is to reduce the risk of the wide field of view visual input to the SLAM system. Based on the conditional probability model, this work reveals the definite impact of the above data properties changes on the optimization process, concretizes it as point uncertainty and pose uncertainty, and gives a specific mathematical form. P2U-SLAM respectively embeds point uncertainty and pose uncertainty into the tracking module and local mapping, and updates these uncertainties after each optimization operation including local mapping, map merging, and loop closing. We present an exhaustive evaluation in 27 sequences from two popular public datasets with wide-FoV visual input. P2U-SLAM shows excellent performance compared with other state-of-the-art methods. The source code will be made publicly available at https://***/BambValley/P2U-SLAM. Copyright © 2024, The Authors. All rights reserved.

关键词： Mapping

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

An Intelligent Route Recommendation Method for Smart Interne...

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Chinese control Conference (CCC)

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

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.

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