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2019 IEEE International Conference on Real-Time Computing and robotics, RCAR 2019

作者： Liu, Xiaofeng Li, Jinming Hu, Fang Yang, Chenguang College of IoT Engineering Hohai University Changzhou213022 China Changzhou Key Laboratory of Robotics and Intelligent Technology Changzhou213022 China Jiangsu Key Laboratory of Special Robots Changzhou213022 China School of Electromechanical and Automobile Engineerng Changzhou Vacational Institue of Engineering Changzhou213164 China Bristol Robotics Laboratory University of the West of England BristolBS16 1QY United Kingdom

ISBN: (纸本)9781728137261

Rapidly-Exploring Random Tree (RRT) has been extensively applied to robot navigation field as a fast and effective path planning method. Rapidly-Exploring Random Tree Star (RRT*), one of the extensions of RRT, outperforms other methods because it can approach the optimal path with the number of iterations increases. Nonetheless, as the number of sampling points increases, it takes too long to get an optimal path and the convergence speed slows dramatically for RRT and all its variants, since the range of sampling is the entire configuration space. In this paper, we propose a novel method of robot path planning in the global knowledge scenario: obstacle induced stochastic tree algorithm. This algorithm regards the center point in obstacles as the sampling point, which significantly reduces the sampling range then shorts the time for path planning. Simulation results demonstrate that our algorithm can find a feasible path at a rapid rate. Compared with RRT and its variants algorithms, the algorithm has better performance in both time and path cost. © 2018 IEEE

关键词： Motion planning

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Using NSGA-Ⅲ for optimising biomedical ontology alignment

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CAAI Transactions on Intelligence technology 2019年第3期4卷 135-141页

作者： Xingsi Xue Jiawei Lu Junfeng Chen College of Information Science and Engineering Fujian University of TechnologyFuzhouFujianPeople’s Republic of China Intelligent Information Processing Research Center Fujian University of TechnologyFuzhouFujianPeople’s Republic of China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of TechnologyFuzhouFujianPeople’s Republic of China Fujian Key Laboratory for Automotive Electronics and Electric Drive Fujian University of TechnologyFuzhouFujianPeople’s Republic of China College of IOT Engineering Hohai UniversityChangzhouJiangsuPeople’s Republic of China

To support semantic inter-operability between the biomedical information systems, it is necessary to determine the correspondences between the heterogeneous biomedical concepts, which is commonly known as biomedical ontology matching. Biomedical concepts are usually complex and ambiguous, which makes matching biomedical ontologies a challenge. Since none of the similarity measures can distinguish the heterogeneous biomedical concepts in any context independently, usually several similarity measures are applied together to determine the biomedical concepts mappings. However, the ignorance of the effects brought about by different biomedical concept mapping’s preference on the similarity measures significantly reduces the alignment’s quality. In this study, a non-dominated sorting genetic algorithm (NSGA)-III-based biomedical ontology matching technique is proposed to effectively match the biomedical ontologies, which first utilises an ontology partitioning technique to transform the large-scale biomedical ontology matching problem into several ontology segment-matching problems, and then uses NSGA-III to determine the optimal alignment without tuning the aggregating weights. The experiment is conducted on the anatomy track and large biomedic ontologies track which are provided by the Ontology Alignment Evaluation Initiative (OAEI), and the comparisons with OAEI’s participants show the effectiveness of the authors’ approach.

关键词： ontology ontologies transform together Ontology complex context effects

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VFH∗ Based Local Path Planning for Mobile Robot 2

VFH∗ Based Local Path Planning for Mobile Robot

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2nd China Symposium on Cognitive Computing and Hybrid Intelligence, CCHI 2019

作者： Chen, Wenqiang Wang, Ning Liu, Xiaofeng Yang, Chenguang Key Laboratory of Autonomous System and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou510640 China Bristol Robotics Laboratory University of the West of England BristolBS16 1QY United Kingdom Changzhou Key Laboratory of Robotics and Intelligent Technology College of Internet of Things Engineering Hohai University Changzhou213022 China

ISBN: (纸本)9781728140919

Vector Field Histogram(VFH) and its variants are effective obstacles avoidance method for mobile robots. Under the more consideration of realistic, we proposed a new local path planning method for mobile robot in this paper. The proposed method takes global path point generated by the A∗ algorithm as temporary target point and adopts the basic concepts of the VFH∗ algorithm, the difference is mainly lies in the representation of vector magnitude of the obstacles, the determination of the threshold, the selection of the candidate direction, and the definition of the node cost function in search tree. Besides, according to the optimal obstacle avoidance direction obtained in the above steps, we also give a speed control method to control the movement of the omnidirectional mobile robot to the target point. Simulation and experiment results shows that the proposed method is suited for mobile robot moving in realistic situation. © 2019 IEEE.

关键词： Mobile robots

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Observer-Based Robust Containment Control of Multi-agent Systems With Input Saturation

Observer-Based Robust Containment Control of Multi-agent Sys...

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第三十九届中国控制会议

作者： Juan Qian Xiaoling Wang Guo-Ping Jiang Housheng Su College of Automation and College of Artificial Intelligence Nanjing University of Posts and Telecommunicationsand Jiangsu Engineering Lab for IOT Intelligent Robots(IOTRobot) School of Artificial Intelligence and Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology

In this paper, the robust containment control problem of the leader-following multi-agent systems with input saturation and input additive disturbance is addressed, where the followers can be informed by multiple leaders. With the help of the lowand-high gain feedback technique and the high-gain observer approach, a distributed control algorithm for each agent is firstly designed by using the observed output information, then sufficient conditions are provided to guarantee the semi-global robust containment of the system. Finally, some numerical simulations are given to verify the correctness of the theoretical results.

关键词： Containment control multi-agent system input saturation input additive disturbance

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Distributed Global Leader-Following Coordination of MASs with Heterogeneous Input Saturation: Scheduling Low-Gain Revisited

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Journal of the Franklin Institute 2025年第11期362卷

作者： Xiaoling Wang Shengnan Zhu Juan Qian Housheng Su College of Automation & AI Nanjing University of Posts and Telecommunications and Jiangsu Engineering Lab for IOT Intelligent Robots (IOTRobot) Nanjing 210023 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai 200237 China Université Claude Bernard Lyon 1 CNRS LAGEPP UMR 5007 43 boulevard du 11 novembre 1918 F-69100 Villeurbanne France National Key Laboratory of Multispectral Information Intelligent Processing Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China

In this paper, we revisit the global coordinated tracking problem of the leader-following multi-agent systems with input saturation via the scheduling low-gain feedback technique, aiming to make breakthroughs from aspects such as the heterogeneity of saturation level and the distributed characteristic of scheduled tuning algorithms on the low-gain parameters, that is the newly proposed distributed scheduling low-gain approach. First, we provide a continuous-time tuning algorithm for the low-gain parameter of each follower to articulate the fundamental idea of the distributed scheduling low-gain technique on addressing heterogeneous saturation, so as to solve the global consensus tracking of multi-agent systems with heterogeneous input saturation and one leader. Then, this result is extended to the global containment tracking of multi-agent systems with multiple leaders. Furthermore, from the perspective of reducing communication burden, we further propose a distributed scheduling low-gain parameter algorithm by using the sampled relative information between each follower and its neighbors, and offer the upper and lower bounds on the sampling period to ensure the achievement of global coordination tracking. Finally, numerical simulations are performed to verify the theoretical results.

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Research and Experimental Verification on Coupling Mechanical Characteristics of Surrounding Rock of Hydraulic Support Group in Comprehensive Working Face

Research Square

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Research Square 2021年

作者： Zhang, Kun Chi, Zengxian Ma, Ying Li, Yu-Xia Feng, Long Li, Teng-Da Xu, Ya-Jun Chen, Hong-Yue Zhang, De-Sheng Huang, Liang-Song Shandong Provincial Key Laboratory of Robotics and Intelligent Technology Shandong University of Science and Technology Qianwangang Road 579 Shandong Province Qingdao266590 China Coal Mining Technology Department Tiandi Science and Technology Co． Ltd． Qingniangou Road 5 Beijing100013 China College of Mechanical Engineering Liaoning Technical University Yulong Road 88 Liaoning Province Fuxin123000 China

The hydraulic support group and the surrounding rock in fully mechanized mining faces often do not exist in isolation;rather, they compose in a mutually coupled system. Research on the mechanical characteristics of roofs under the support of group supports can lay a foundation for the determination of the ideal support strength of group support equipment. This paper establishes a coupled mechanical model of the surrounding rock of hydraulic support groups in a fully mechanized mining face. Through variable parameter calculations, the influence of different roof elastic moduli, mining heights, working face lengths, end face distances, support stiffnesses, coal wall stiffnesses and direct roof thicknesses on roof deformation is analyzed, and the corresponding ideal support strength of a hydraulic support is given. The results show that: the deformation of the roof and the ideal support strength of the hydraulic support group decrease as the elastic modulus of the roof increase;the deformation amount of the roof and the ideal support strength of the hydraulic support group increase as the mining height increases;the deformation amount of the roof and the ideal support strength of the hydraulic support group increase as the working face length increases;the deformation amount of the roof and the hydraulic support group also increase. The results also show that the ideal support strength of the support group decreases as the face distance of the top beam end increases;the deformation of the roof decreases significantly as the equivalent stiffness of the hydraulic support group increases, but the ideal support strength of the hydraulic support group increases significantly;the deformation amount of the roof and the ideal support strength of the hydraulic support group decrease significantly as the equivalent stiffness of the coal wall increases;and the deformation amount of the roof and the hydraulic support are significantly reduced. The ideal support strength of the sup

关键词： Roofs

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An MR Safe Rotary Encoder Based on Eccentric Sheave and FBG Sensors

An MR Safe Rotary Encoder Based on Eccentric Sheave and FBG ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Shaoping Huang Anzhu Gao Zicong Wu Chuqian Lou Yanjun Wang Guang-Zhong Yang The Institute of Medical Robotics and School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China Shanghai Jiao Tong University The Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China The Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China The Imperial College London and Empa-Swiss Federal Laboratories for Materials Science and Technology

MRI-guided robotic systems are emerging platforms for minimally invasive intervention because of high positioning accuracy and excellent tissue contrast. MR safe encoders are critical components for closed-loop robotic control. This paper develops an MR safe absolute rotary encoder based on eccentric sheave and FBG sensors. The eccentric sheave transforms the rotational motion of the shaft to the bending deflection of the beam on which FBG sensors are integrated. A model is built by establishing the relationship of the kinematics of the sheave, the mechanical properties of the beam with unknown length, and the strain model of two Fiber Bragg Grating (FBG) sensors. A Pseudo-Rigid Body (PRB) 3R model is used to solve a set of constrained equations for accurate rotary encoding. A prototype is built to calibrate the parameters and validate the accuracy of the encoder and its MR compatibility. Results show that the maximum angular error is 1.6°, and the RMS error is 0.46°. MRI shows that no noticeable artifacts are observed, and the Signal to Noise Ratio (SNR) is not affected. The results demonstrate the potential of the proposed method for it to be integrated with MR safe robots with easy fabrication, compact structures, and continuous measurement.

关键词： Mechanical sensors Shafts Analytical models Kinematics Transforms Fiber gratings Robot sensing systems

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Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Services

arXiv

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arXiv 2023年

作者： Xu, Minrui Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Mao, Shiwen Han, Zhu Jamalipour, Abbas Kim, Dong In Shen, Xuemin Leung, Victor C.M. Poor, H. Vincent The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore The School of Automation Guangdong University of Technology Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education Guangzhou510006 China Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore487372 Singapore The Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States The Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of The School of Electrical and Information Engineering University of Sydney SydneyNSW2006 Australia The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of The Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada The College of Computer Science and Software Engineering Shenzhen University Shenzhen518061 China The Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

Artificial Intelligence-Generated Content (AIGC) is an automated method for generating, manipulating, and modifying valuable and diverse data using AI algorithms creatively. This survey paper focuses on the deployment of AIGC applications, e.g., ChatGPT and Dall-E, at mobile edge networks, namely mobile AIGC networks, that provide personalized and customized AIGC services in real time while maintaining user privacy. We begin by introducing the background and fundamentals of generative models and the lifecycle of AIGC services at mobile AIGC networks, which includes data collection, training, fine-tuning, inference, and product management. We then discuss the collaborative cloud-edge-mobile infrastructure and technologies required to support AIGC services and enable users to access AIGC at mobile edge networks. Furthermore, we explore AIGC-driven creative applications and use cases for mobile AIGC networks. Additionally, we discuss the implementation, security, and privacy challenges of deploying mobile AIGC networks. Finally, we highlight some future research directions and open issues for the full realization of mobile AIGC networks. © 2023, CC BY.

关键词： Life cycle

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Position Sensorless Control of Permanent Magnet Synchronous Motor Based on Adaptive Sliding Mode Observer

Position Sensorless Control of Permanent Magnet Synchronous ...

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Chinese Automation Congress (CAC)

作者： Tao Zhang Yingjie Xiong Bolun Wang Hongyu Yan Xiyou Chen School of Electrical Engineering Dalian University of Technology Dalian China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China College Of Information Science and Engineering Northeastern University Shenyang China School of Artificial Intelligence Shenyang University of Technology Shenyang China

ISBN: (纸本)9781665426480

Permanent magnet synchronous motors(PMSM) are popular in AC motor applications due to their small size, high efficiency. They have appeared widely in various areas of life. Due to the high-frequency chattering problem caused by sliding mode observer sensorless control of PMSM, an SMO with piecewise control function is designed in this paper. At the same time, based on the back EMF output of the SMO, the gain of the SMO is adapted to reduce the system bucket vibration problem caused by the conventional SMO. Finally, a simulation experiment was carried out in MATLAB/SIMULINK and compared with the conventional SMO. The results show that the improved SMO has achieved a better control effect.

关键词： Vibrations Adaptation models AC motors Force Sensorless control Observers Permanent magnet motors

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Super-resolving Compressed Images via Parallel and Series Integration of Artifact Reduction and Resolution Enhancement

arXiv

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arXiv 2021年

作者： Luo, Hongming Zhou, Fei Liao, Guangsen Qiu, Guoping College of Electronics and Information Engineering Shenzhen University China Peng Cheng Laboratory Shenzhen China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen China Shenzhen Key Laboratory of Digital Creative Technology China Shenzhen Institute for Artificial Intelligence and Robotics for Society Shenzhen China School of Computer Science University of Nottingham NottinghamNG8 1BB United Kingdom Guangdong-Hong Kong Joint Laboratory for Big Data Imaging and Communication Guangdong Shenzhen China

In real-world applications, such as sharing photos on social media platforms, images are always not only sub-sampled but also heavily compressed thus often containing various artefacts. Simple methods for enhancing the resolution of such images will exacerbate the artefacts, rendering them visually objectionable. In spite of its high practical values, super-resolving compressed images is not well studied in the literature. In this paper, we propose a novel compressed image super resolution (CISR) framework based on parallel and series integration of artefacts removal and resolution enhancement. Based on a mathematical inference model for estimating a clean low-resolution (LR) image and a clean high-resolution (HR) image from a down-sampled and compressed observation, we have designed a CISR architecture consisting of two deep neural network modules: the artefacts removal module (ARM) and the resolution enhancement module (REM). The ARM and the REM work in parallel with both taking the compressed LR image as their inputs, at the same time they also work in series with the REM taking the output of the ARM as one of its inputs and the ARM taking the output of the REM as its other input. A technique called unfolding is introduced to recursively suppress the compression artefacts and restore the image resolution. A unique feature of our CISR system is that it exploits the parallel and series connections between the ARM and the REM, and recursive optimization to reduce the model's dependency on specific types of degradation thus making it possible to train a single model to super-resolve images compressed by different methods to different qualities. Experiments are conducted on a mixture of JPEG and WebP compressed images without assuming apriori compression type and compression quality factor. To demonstrate our technique's real-world application value, we have also applied the trained models directly to restore social media images which have undergone scaling and compre

关键词： Deep neural networks

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