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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Liu, Nannan Wang, Tong Wang, Jianmin Fan, Yingda School of Electronic and Information Engineering Ningbo University of Technology Ningbo China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China Department of Computer Science University of Pittsburgh Pittsburgh United States

ISBN: (纸本)9781665464543

To minimize the disturbance of the Tunnel Boring Machine (TBM) cutterhead on the surrounding rock during the coal mine roadway excavation process and ensure that the cutterhead rotation speed achieves fast tracking performance with minimal overshoot, we propose a direct adaptive robust control method for the cutterhead rotation speed hydraulic system based on inversion design. This method considers the strong disturbances such as loads and motion affecting the cutterhead hydraulic drive system, as well as the uncertainties in the cutterhead model. We establish the nonlinear model of the cutterhead hydraulic drive system and employ virtual control to reduce the model order. Using Lyapunov functions, we ensure the stability of the entire system and derive the control law for the cutterhead rotation speed controller, along with parameter-adaptive laws acting as parameter estimators. We validate the effectiveness of the proposed control strategy through joint simulation using AMESim and Simulink. The results show that the designed cutterhead rotation speed controller achieves high tracking accuracy and good adaptability. © 2024 IEEE.

关键词： Hydraulic drives

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When LoRa meets distributed machine learning to optimize the network connectivity for green and intelligent transportation system

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Green Energy and intelligent Transportation 2024年第3期3卷 24-41页

作者： Malak Abid Ali Khan Hongbin Ma Arshad Farhad Asad Mujeeb Imran Khan Mirani Muhammad Hamza National Key Lab of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Computer Science Namal UniversityPakistan Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Faculty of Information Technology Beijing University of TechnologyBeijing 100124China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China

LoRa technology contributes to green energy by enabling efficient,long-range communication for the Internet of Things(IoT).This paper addresses the challenges related to coverage range in outdoor monitoring systems utilizing LoRa,where the network performance is affected by the density of gateways(GWs)and end devices(EDs),as well as environmental *** mitigate interference,data throughput losses,and high-power consumption,the proposed spreading factor(SF)and hybrid(data rate|SF)models dynamically adjust the transmission *** orchestration of concurrent data modifications within the network server(NS)is crucial for uninterrupted communication between GWs and EDs,especially in monitoring electric vehicle(EV)stations to reduce traffic congestion and *** K-means and density-based spatial clustering of applications with noise(DBSCAN)algorithms optimizes ED allocation,averts data congestion,and improves the signal-tointerference noise ratio(SINR).These methods ensure seamless information reception by meticulously allocated EDs across various GW *** estimate the free-space losses(FSL),a log-distance path loss model(log-PL)is *** various bandwidths(BWs),bidirectional communications,and duty cycles(DCs)helps to prevent saturation,thus prolonging the operational lifespan of *** findings reveal a notable packet rejection rate(PRR)of 0%for the DBSCAN(hybrid model).In contrast,the K-means exhibits a PRR ranging from 5%(hybrid model)to 35.29%(SF model)for the ten GWs ***,the network saturation is reduced to 10.185%and 9.503%,respectively,highlighting an improvement in the average efficiency of slotted ALOHA(91.1%)and pure ALOHA(90.7%).These enhancements increase the lifespan of EDs to 15,465.27 days.

关键词： DBSCAN Green transportation Hybrid model intelligent transportation K-means

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Vision Transformer-enabled Semantic Segmentation for Enhanced Robotic Grasping in 3D Space 20

Vision Transformer-enabled Semantic Segmentation for Enhance...

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20th IEEE India Council International Conference, INDICON 2023

作者： Shukla, Shivam Singh, Aditya Kushwaha, Vandana Nandi, G.C. Indian Institute of Information Technology Center of Intelligent Robotics U.P. Allahabad211015 India Universitat Rovira i Virgili Tarragona Spain

ISBN: (纸本)9798350305593

In recent years, the integration of computer vision and robotics has gathered significant interest in automating a range of tasks, including object detection and robotic grasping in 3D space. This research paper introduces an innovative approach to enhance robotic grasping in 3D space by leveraging unsupervised semantic segmentation using a Vision Transformer (ViT) based architecture. The proposed method utilizes a deep learning architecture to segment objects in the scene and incorporates a grasp detection module to identify potential grasping rectangles based on the segmented objects. The model is trained on a large-scale dataset, enabling it to generalize effectively across various objects and environments. The paper also addresses the utilization of 2D bounding box and point cloud data to facilitate 3D object localization. The proposed approach is evaluated using the Cornell Grasping Dataset, achieving a remarkable success rate of 87.7% for grasping rectangles. Furthermore, by leveraging the 2D bounding box generated by the model alongside corresponding point cloud data, the method estimates the object's height and orientation, leading to the generation of a comprehensive 3D bounding box. This paper presents a robust and efficient method for robotic grasping and 3D object localization by harnessing the capabilities of computer vision and deep learning techniques. © 2023 IEEE.

关键词： Grasping Rectangle Object Localization Unsupervised Semantic Segmentation

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Human-Centric Concept for a Reconfigurable Robotic System Enabling Low-Volume Assembly of Photonic and Quantum Modules

Human-Centric Concept for a Reconfigurable Robotic System En...

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2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Wicht, Andreas Franke, Tobias Hahn, Alina Hakansson, Nils Kurbis, Christian Smol, Robert Hulin, Thomas Eiband, Thomas Lehner, Peter Muhlbauer, Maximilian Nottensteiner, Korbinian Pietschmann, Richard Thaler, Bernhard Thaler, Diana Bosse, Jurgen Berlin12489 Germany Institute of Robotics and Mechatronics Wessling82234 Germany Germany Technical University of Munich Sensor Based Robotic Systems and Intelligent Assistance Systems Garching85748 Germany Robo-Technology GmbH Puchheim82178 Germany

ISBN: (纸本)9798331531614

This paper presents a novel concept for a reconfigurable robotic system specifically designed to meet the demands of hybrid integration for miniaturized photonic and quantum System-in-Packages (SiPs). The proposed solution introduces a distinctive approach to ultra-high-resolution, multi-telerobotic assembly and inspection. By integrating key Industry 5.0 principles, it establishes a human-centric control framework that minimizes both physical and cognitive stress while ensuring the human operator remains in full control at all *** robotic system features eight robots working simultaneously within a compact footprint of just 5×10 cm2. A comprehensive digital twin framework constitutes a central element of the robotic system. It encompasses the robotic workcell, the SiP under assembly, and the components to be integrated, ensuring precise adherence to design specifications. Key functionalities include automated path planning in a multi-robotic environment, collision avoidance in a densely packed workcell, and virtual fixtures to guide teleoperation, enhancing the operator's control and interaction through advanced and intuitive human-machine interfaces (HMI). The proposed system meets the critical demands of ultra-high-resolution assembly for complex, high-value SiPs, providing high flexibility and ease of operation for small-batch manufacturing. © 2025 IEEE.

关键词： System-in-package

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3D fully-enclosed triboelectric nanogenerator with bionic fish-like structure for harvesting hydrokinetic energy

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Nano Research 2022年第6期15卷 5098-5104页

作者： Zhaoxu Jing Jiacheng Zhang Jianlong Wang Mingkang Zhu Xinxian Wang Tinghai Cheng Jianyang Zhu Zhong Lin Wang Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of SciencesBeijing 101400China School of Mechatronic Engineering Changchun University of TechnologyChangchunJilin 130012China Institute of Robotics and Intelligent Systems Wuhan University of Science and TechnologyWuhanHubei 430081China CUSTech Institute of Technology WenzhouZhejiang 325024China School of Materials Science and Engineering Georgia Institute of TechnologyAtlantaGA 30332-0245USA

The hydrokinetic energy of river current,as one of the essential and widespread renewable energies,is difficult to be harvested in low flow velocity and shallow water *** this work,a three-dimensional(3D)fully-enclosed triboelectric nanogenerator(FETENG)with bionic fish-like structure for harvesting hydrokinetic energy is reported,which is comprised of the triboelectric powergeneration unit,bionic fish-like structure and connection *** the bionic structure,the FE-TENG realizes zero head power generation in shallow water with low flow ***’s more,the effect of external excitations and bionic structures on the electrical performance are systematically studied in this *** FE-TENG can generate peak power density of 7 and 0.36 W/m^(3)respectively under the simulated swing state with frequency of 1.25 Hz and simulated river current with flow velocity of 0.81 m/*** practical applications,due to the 3D fully-enclosed design,the FE-TENG immersed in water for 35 days demonstrates excellent immersion durability with undiminished electrical ***,the work proposes an efficient method realizing zero head power generation,and provides a good candidate for long-term service in the river current.

关键词： hydrokinetic energy three-dimensional(3D)fully-enclosed design triboelectric nanogenerator bionic fish-like structure zero head power generation water immersion durability

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Probing Local Cellular Mechanics by Atomic Force Microscopy with Modified Spherical Tip

Probing Local Cellular Mechanics by Atomic Force Microscopy ...

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2022 IEEE International Conference on Cyborg and Bionic systems, CBS 2022

作者： Zuo, Zhaofeng Liu, Xiaoming Tang, Xiaoqing Liu, Fengyu Liu, Dan Li, Yuyang Huang, Qiang Arai, Tatsuo Beijing Institute of Technology Beijing Adv. Innov. Ctr. for Intelligent Robots and Systems The Intelligent Robotics Inst. School of Mechatronical Engineering Beijing100081 China

ISBN: (纸本)9781665490283

The mechanical characterization of cell is important for knowing the physiological state and studying diseases of organism. While many approaches are available for measuring cellular elasticity, distinguishing the stiffness variation among different cellular areas is still a challenge. In this paper, we reported a method to modify spherical atomic force microscopy (AFM) tip for accurate measurement of Young's modulus in several areas on single adherent living cancer cells (Hela cells). The micrometer size spheres were transported to an AFM probe tip by dual micropipettes and fixed by ultraviolet (UV) curable glue, which is reproducible and nondestructive to the cantilever. The force-displacement curves were measured along major axis of cells with the modified AFM probe in indentation experiments. The results demonstrate that the modulus value increased with the detected point approaching the nucleus center, and areas closed to nucleus showed have higher stiffness. Our study provides a quantitative method for static measurement of different locations of cell, and the result has the potential to reveal how intracellular structures have effect on the cell mechanical characterization. © 2023 IEEE.

关键词： Probes

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Near-Space Communications: The Last Piece of 6G Space–Air–Ground–Sea Integrated Network Puzzle

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Space(Science & technology) 2024年第1期4卷 183-203页

作者： Hongshan Liu Tong Qin Zhen Gao Tianqi Mao Keke Ying Ziwei Wan Li Qiao Rui Na Zhongxiang Li Chun Hu Yikun Mei Tuan Li Guanghui Wen Lei Chen Zhonghuai Wu Ruiqi Liu Gaojie Chen Shuo Wang Dezhi Zheng School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of CNS/ATM Beijing Institute of TechnologyBeijing 100081China MIIT Key Laboratory of Complex-Field Intelligent Sensing Beijing Institute of TechnologyBeijing 100081China Beijing Institute of Technology(Zhuhai) Zhuhai 519088China Advanced Technology Research Institute Beijing Institute of TechnologyJinan 250307China Yangtze Delta Region Academy Beijing Institute of Technology(Jiaxing)Jiaxing 314019China Department of Systems Science Southeast UniversityNanjing 210096China Beijing Key Laboratory for Precision Optoelectronic Measurement Instrument and Technology School of Optics and PhotonicsBeijing Institute of TechnologyBeijing 100081China Wireless and Computing Research Institute ZTE CorporationBeijing 100029China G/6G Innovation Centre Institute for Communication SystemsUniversity of SurreyGU27XH GuildfordUK China Academy of Space Technology Beijing 100094China

This article presents a comprehensive study on the emerging near-space communications (NS-COM) within the context of space–air–ground–sea integrated network (SAGSIN). Specifically, we firstly explore the recent technical developments of NS-COM, followed by the discussions about motivations behind integrating NS-COM into SAGSIN. To further demonstrate the necessity of NS-COM, a comparative analysis between the NS-COM network and other counterparts in SAGSIN is conducted, covering aspects of deployment, coverage, channel characteristics, and unique problems of NS-COM network. Afterward, the technical aspects of NS-COM, including channel modeling, random access, channel estimation, array-based beam management, and joint network optimization, are examined in detail. Furthermore, we explore the potential applications of NS-COM, such as structural expansion in SAGSIN communication, civil aviation communication, remote and urgent communication, weather monitoring, and carbon neutrality. Finally, some promising research avenues are identified, including stratospheric satellite-to-ground direct links for mobile terminals, reconfigurable multiple-input multiple-output and holographic multiple-input multiple-output, federated learning in NS-COM networks, maritime communication, electromagnetic spectrum sensing and adversarial game, integrated sensing and communications, stratospheric-satellite-based radar detection and imaging, NS-COM-assisted enhanced global navigation system, NS-COM-assisted intelligent unmanned system, and free-space optical communication. Overall, this paper highlights that the NS-COM plays an indispensable role in the SAGSIN puzzle, providing substantial performance and coverage enhancement to the traditional SAGSIN architecture.

关键词： comparative analysis random access near space communications channel modeling joint network optimization array based beam management space air ground sea integrated network channel estimation

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Gas distribution mapping based on integrating system with mobile robot and sensor network 41

Gas distribution mapping based on integrating system with mo...

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第41届中国控制会议

作者： Zhirui Xu Lei Cheng Daiwei Tang Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The monitoring of industrial environmental gas quality becomes an increasingly important topic due to its significant impact on the health of the producers and the safety of the production ***,there are two main approaches to this task:first,using mobile robots equipped with sensors to patrol and monitor the environment,the prediction accuracy of this method is relatively poor;second,using a sensor network distributed in the environment for a long term monitoring,however this method lefts spatial relations and non-detection areas *** solve the above problems,this paper proposes a method combining the spatial map constructed by the mobile robot with fixed monitoring *** this method,the concentration of gas is collected by a fixed gas sensor and predicted by a deep neural *** the same time,a mobile robot equipped with lidar and a gas sensor is used to model the spatial construction of the environment as well as verify the *** embedding the predicted concentration map with the spatial map,a gas concentration map with high accuracy and spatial information is *** using anhydrous ethanol odor sources in a closed and windless room showed high prediction accuracy(98%) with this method.

关键词： Gas distribution mapping Deep neural networks spatial-temporal distribution simultaneous Localization and Mapping(SLAM)

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Experimental demonstration of reconstructing quantum states with generative models

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Science Bulletin 2025年第10期70卷 1572-1575页

作者： Li, Xuegang Jiang, Wenjie Hua, Ziyue Wang, Weiting Pan, Xiaoxuan Cai, Weizhou Lu, Zhide Han, Jiaxiu Wu, Rebing Zou, Chang-Ling Deng, Dong-Ling Sun, Luyan Center for Quantum Information Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Shanghai Qi Zhi Institute Shanghai200232 China Center for Intelligent and Networked Systems Department of Automation Tsinghua University Beijing100084 China Hefei National Laboratory Hefei230088 China CAS Key Laboratory of Quantum Information University of Science and Technology of China Hefei230026 China

Highlights • Experimental demonstration of quantum state reconstruction with generative models. • RNN-based model efficiently learns quantum states from experimental data. • Linear resource scaling outperforms traditi...

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Label-Consistent Convolutional Dictionary Learning for Machine Inspection 31

Label-Consistent Convolutional Dictionary Learning for Machi...

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31st European Signal Processing Conference, EUSIPCO 2023

作者： Sahu, Saurabh Kumar, Kriti Majumdar, Angshul Kumar, A. Anil Chandra, M. Girish Embedded Devices and Intelligent Systems TCS Research Bangalore India Indraprastha Institute of Information Technology Delhi New Delhi India

ISBN: (纸本)9789464593600

Machine fault diagnosis is crucial for predicting and preventing unexpected failures. In most practical application scenarios of machine inspection, access to data is limited. Moreover, the labeled instances are few, which makes it challenging for the existing data-driven techniques to learn efficient representations. To address this issue, we propose a novel label-consistent convolutional dictionary learning for machine fault classification. This method employs a joint optimization formulation for learning the dictionary atoms, corresponding coefficients, and weights associated with a label-consistency term. The label-consistency term added in the joint formulation helps in learning class-discriminative dictionaries. The features generated from the class-discriminative dictionaries result in robust inferencing when used with an external classifier. The performance of the proposed method is evaluated using the publicly available CWRU dataset for bearing fault diagnosis. The results demonstrate the superior performance of the proposed method compared to other state-of-the-art deep learning and dictionary learning techniques for the data limited scenario. Furthermore, with only 10% of training data, the proposed method achieved an accuracy of around 85%, while the other methods provided less than 50%. © 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.

关键词： Failure analysis

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