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International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)

作者： Buzhen Huang Yuan Shu Tianshu Zhang Yangang Wang Southeast University China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China

ISBN: (纸本)9781665426893

Dynamic multi-person mesh recovery has been a hot topic in 3D vision recently. However, few works focus on the multi-person motion capture from uncalibrated cameras, which mainly faces two challenges: the one is that inter-person interactions and occlusions introduce inherent ambiguities for both camera calibration and motion capture; The other is that a lack of dense correspondences can be used to constrain sparse camera geometries in a dynamic multi-person scene. Our key idea is incorporating motion prior knowledge into simultaneous optimization of extrinsic camera parameters and human meshes from noisy human semantics. First, we introduce a physics-geometry consistency to reduce the low and high frequency noises of the detected human semantics. Then a novel latent motion prior is proposed to simultaneously optimize extrinsic camera parameters and coherent human motions from slightly noisy inputs. Experimental results show that accurate camera parameters and human motions can be obtained through one-stage optimization. The codes will be publicly available at https://***.

关键词： Geometry Three-dimensional displays Semantics Dynamics Cameras Calibration Noise measurement

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Automatic steel grabbing robot system for scrap steel processing production line

Automatic steel grabbing robot system for scrap steel proces...

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IEEE International Conference on Robotics and Biomimetics

作者： Rongsheng Wang Bo Zhou Yirong Liu Fang Fang Zeqing Chang Yuyao Sun Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing P.R. China

ISBN: (纸本)9781665405362

Steel grabbing robot, which is a breed of robotic excavator driven by hydraulic system, has been manipulated by industrial workers to grab scrap steel for many years. In order to solve equipment loss and operational problems due to nonstandard manual operations and unsystematic managements during the grabbing process, this paper designs an automatic steel grabbing robot system, which consists of grabbing robot prototype’s hardware architecture, forward and reverse kinematics analysis and trajectory planning of joint-space schemes and Cartesian-space schemes for actual application scenarios. Moreover, Simulations are carried out using MATLAB, which demonstrate the correctness and efficiency of the system.

关键词： Interpolation Service robots Trajectory planning systems architecture Kinematics Production Hardware

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Application of Hybrid Energy Storage Device in High Power Direct-current Power Supply 17

Application of Hybrid Energy Storage Device in High Power Di...

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17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Liu, Yue Wang, Chunjie Chen, Peng Yin, Jinliang School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin Complex System Control Theory and Application Key Laboratory Tianjin China

ISBN: (纸本)9781728164151

The drop-away current of 1500V low-voltage direct-current circuit breaker used in metro DC traction power supply system needs to be checked regularly. The instantaneous power is very high when the detection device is working, and the field power supply is often difficult to meet the requirements. Therefore, an energy storage unit is needed to supply power to the detector. In this paper, a design scheme of high-power DC power supply with supercapacitor and battery as energy storage is proposed, and the energy management and discharge control strategies are studied in theory and simulation, which verify the effectiveness and feasibility of the scheme. © 2020 IEEE.

关键词： Drops

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Efficient IoT Devices Localization Through Wi-Fi CSI Feature Fusion and Anomaly Detection

arXiv

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arXiv 2024年

作者： Li, Yan Yang, Jie Shih, Shang-Ling Shih, Wan-Ting Wen, Chao-Kai Jin, Shi The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Frontiers Science Center for Mobile Information Communication and Security Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China The Institute of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan The National Mobile Communications Research Laboratory Southeast University Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China

Internet of Things (IoT) device localization is fundamental to smart home functionalities, including indoor navigation and tracking of individuals. Traditional localization relies on relative methods utilizing the positions of anchors within a home environment, yet struggles with precision due to inherent inaccuracies in these anchor positions. In response, we introduce a cutting-edge smartphone-based localization system for IoT devices, leveraging the precise positioning capabilities of smartphones equipped with motion sensors. Our system employs artificial intelligence (AI) to merge channel state information from proximal trajectory points of a single smartphone, significantly enhancing line of sight (LoS) angle of arrival (AoA) estimation accuracy, particularly under severe multipath conditions. Additionally, we have developed an AI-based anomaly detection algorithm to further increase the reliability of LoS-AoA estimation. This algorithm improves measurement reliability by analyzing the correlation between the accuracy of reversed feature reconstruction and the LoS-AoA estimation. Utilizing a straightforward least squares algorithm in conjunction with accurate LoS-AoA estimation and smartphone positional data, our system efficiently identifies IoT device locations. Validated through extensive simulations and experimental tests with a receiving antenna array comprising just two patch antenna elements in the horizontal direction, our methodology has been shown to attain decimeter-level localization accuracy in nearly 90% of cases, demonstrating robust performance even in challenging real-world scenarios. Additionally, our proposed anomaly detection algorithm trained on Wi-Fi data can be directly applied to ultra-wideband, also outperforming the most advanced techniques. Copyright © 2024, The Authors. All rights reserved.

关键词： Smartphones

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Interpretable analysis of feature importance and implicit correlation based on sEMG grayscale. images

Interpretable analysis of feature importance and implicit co...

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Industrial Cyber-Physical systems (ICPS)

作者： Xiaohu AO Feng Wang Juan Zhao Jinhua She School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan

For patients requiring upper limb rehabilitation, the hand rehabilitation robot assists the patient in completing movements within a certain training trajectory to achieve therapeutic results. There have been studies based on deep learning to convert surface electromyography (sEMG) signals into sEMG images for motion intention analysis. Although good recognition accuracy has been achieved, the working principle of neural networks and the processing of image features by the networks are not well explained. The interpretability of deep neural networks determines human confidence in neural network decisions. In this paper, we design a method based on feature importance and implicit correlation for hand motion intention recognition, experimentally explored that convolutional neural networks have implicit definitions for sEMG grayscale images of the same hand gesture action, and verified the effectiveness of the designed method.

关键词： Deep learning Analytical models Correlation Image recognition Neural networks Thumb Gray-scale

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Fourier Transform-based Wavenumber Domain 3D Imaging in RIS-aided Communication systems

arXiv

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arXiv 2024年

作者： Huang, Yixuan Yang, Jie Tang, Wankai Wen, Chao-Kai Jin, Shi The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education The Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China The National Mobile Communications Research Laboratory The Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China The Institute of Communications Engineering National Sun Yat-Sen University Kaohsiung80424 Taiwan

Radio imaging is rapidly gaining prominence in the design of future communication systems, with the potential to utilize reconfigurable intelligent surfaces (RISs) as imaging apertures. Although the sparsity of targets in three-dimensional (3D) space has led most research to adopt compressed sensing (CS)-based imaging algorithms, these often require substantial computational and memory burdens. Drawing inspiration from conventional Fourier transform (FT)-based imaging methods, our research seeks to accelerate radio imaging in RIS-aided communication systems. To begin, we introduce a two-stage wavenumber domain 3D imaging technique: first, we modify RIS phase shifts to recover the equivalent channel response from the user equipment to the RIS array, subsequently employing traditional FT-based wavenumber domain methods to produce target images. We also determine the diffraction resolution limits of the system through k-space analysis, taking into account factors including system bandwidth, transmission direction, operating frequency, and the angle subtended by the RIS. Addressing the challenge of limited pilots in communication systems, we unveil an innovative algorithm that merges the strengths of both FT- and CS-based techniques by substituting the expansive sensing matrix with FT-based operators. Our simulation outcomes confirm that our proposed FT-based methods achieve high-quality images while demanding few time, memory, and communication resources. Copyright © 2024, The Authors. All rights reserved.

关键词： Fourier transforms

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RIS-aided Single-frequency 3D Imaging by Exploiting Multi-view Image Correlations

arXiv

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arXiv 2024年

作者： Huang, Yixuan Yang, Jie Wen, Chao-Kai Jin, Shi The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education The Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China The Institute of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan The National Mobile Communications Research Laboratory The Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China

Retrieving range information in three-dimensional (3D) radio imaging is particularly challenging due to the limited communication bandwidth and pilot resources. To address this issue, we consider a reconfigurable intelligent surface (RIS)-aided uplink communication scenario, generating multiple measurements through RIS phase adjustment. This study successfully realizes 3D single-frequency imaging by exploiting the near-field multi-view image correlations deduced from user mobility. We first highlight the significance of considering anisotropy in multi-view image formation by investigating radar cross-section properties and diffraction resolution limits. We then propose a novel model for joint multi-view 3D imaging that incorporates occlusion effects and anisotropic scattering. These factors lead to slow image support variation and smooth coefficient evolution, which are mathematically modeled as Markov processes. Based on this model, we employ the Expectation Maximization-Turbo-Generalized Approximate Message Passing algorithm for joint multi-view single-frequency 3D imaging with limited measurements. Simulation results reveal the superiority of joint multi-view imaging in terms of enhanced imaging ranges, accuracies, and anisotropy characterization compared to single-view imaging. Combining adjacent observations for joint multi-view imaging enables a reduction in the measurement overhead by 80%. Copyright © 2024, The Authors. All rights reserved.

关键词： Anisotropy

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An Improved Task Planning Method for Unmanned Swarms with Coupled Physical and Logical Constraints

An Improved Task Planning Method for Unmanned Swarms with Co...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Xiubin Chen Lei Zhang Fang Xu Weiran Yao School of Astronautics Harbin Institude of Technology Harbin China Wuhan 2nd Ship Design and Research Institute Wuhan China Marine Military Intelligence Innovation Institute CSSC Systems Engineering Research Institute Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

Traditional task allocation methods for unmanned swarm systems ignore the effects of actual paths, resulting in estimation accuracy reduction. This paper formulates task planning problem by incorporating physical and logical constraints, and establishes an integrated framework of task allocation and path planning. Conflict-based search method is used to address path planning with physical constraints. A genetic algorithm is employed to solve multi-traveling salesman allocation problem. A bounded suboptimal optimization, a data dictionary, and an island model are introduced to accelerate the convergence speed of the genetic algorithm. The experiments verify that compared to the decoupled task planning methods, the proposed method improves task execution efficiency and remains adaptability to various complex spatial maps.

关键词： Dictionaries Search methods Estimation Path planning Data models Planning Resource management Optimization Genetic algorithms Convergence

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Capacity Optimization of a Hybrid Energy Storage system Considering Wind-Solar Reliability Evaluation Based on a Novel Multi-Strategy Snake Optimization Algorithm

SSRN

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SSRN 2022年

作者： Wang, Chen Jiao, Shangbin Li, Yujun Zhang, Qing School of Automation and Information Engineering Xi’an University of Technology Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China

When the capacity configuration of a hybrid energy storage system (HESS) is optimized considering the reliability of a wind turbine and photovoltaic generator (PVG), the sequential Monte Carlo method is typically adopted to simulate the normal operation and fault probability of wind turbines and PVG units. The capacity optimization configuration model of the HESS is constructed with the life cost cycle (LCC) as an objective and the loss of power supply probability (LPSP) as constraints. The variational mode decomposition is used to decompose the unbalanced power in the wind-PV microgrid. The maximum power of the optimized the battery bank and the supercapacitor bank are used to determine the frequency division point, and the high-frequency power and low-frequency power are respectively allocated to the supercapacitor bank and the battery bank. When the snake optimizer (SO) is used to solve the nonconvex capacity optimization configuration model of the HESS, poor accuracy and stability are significant problems. The opposition-based learning, adaptive weight factor, and Lévy flight strategy are introduced in the algorithm framework. Twenty-three test functions show that multi strategy snake optimizer (MSO) significantly improves the accuracy and convergence speed compared with SO. Nine optimization algorithms including MSO are used to solve the capacity optimization problem of the HESS. The results show that MSO is superior to other algorithms in performance and numerical accuracy. It can reduce the LCC 4.5% and ensure that the capacity of the HESS meets the load demand when the wind turbine and PVGs are in a fault state. © 2022, The Authors. All rights reserved.

关键词： Variational mode decomposition

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Variable impedance control method for robot contact force based on TD3 algorithm

Variable impedance control method for robot contact force ba...

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Chinese Automation Congress (CAC)

作者： Xin Shen Kaiwei Ma Mingxing Yang Shuang Gao Shuo Chao Fengyu Xu College of Automation and College of Artificial Intelligence Nanjing University of Posts and Telecommunications Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Anhui Province Key Laboratory of Special Heavy Load Robot Maanshan China

As a common method of traditional force control, impedance control has been widely used in robot machining field. However, impedance control with fixed parameters cannot dynamically adapt to the manufacturing environment. This paper presents a variable impedance control method for contact forces based on the TD3 (Twin Delayed Deep Deterministic Policy Gradient) algorithm. The method builds on the original impedance model to obtain the optimal impedance parameters for each stage by stochastic exploration of the continuous action space, reducing the reliance on human experience and multiple attempts in the selection of traditional impedance parameters. In this paper, gantry robot is taken as the research object. The simulation results show that the variable impedance control method has faster adjustment time and more stable, and the average position tracking error is about 0.11cm and the force tracking error is about 0.01N.

关键词： Adaptation models Heuristic algorithms Simulation Force Neural networks Stochastic processes Process control

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