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第42届中国控制会议

作者： Minghao Chen En Li Feng Zhang Rui Guo Zize Liang Yuwei Zhang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences The School of Artificial Intelligence University of Chinese Academy of Sciences Shandong Luneng Intelligence Technology Co. Ltd. The State Grid Shandong Electric Power Company

With the remarkable development of the power grid, traditional manual maintenance modes cannot meet the requirement of efficiency and reliability. Robotic technology is applied for power line maintenance to bring down risks and ensure inspectors' safety. Based on the power transmission line maintenance platform, a 5-DOF manipulator is designed to perform the maintenance tasks for the quad bundle conductors. Then the kinematics analysis of the manipulator is analyzed. The manipulator doesn't meet the Pieper criterion. So an improved adaptive particle swarm optimization(APSO) is proposed for figuring out the inverse kinematics. The weights of the pose and the constraint of the prismatic joint are introduced to the algorithm. What's more, half of the particles are initialized around the incipient value of joints and half of the particles are randomly initialized with the constraint of joints in this algorithm. Results show that the manipulator is able to work in the environment of quad bundle conductors and the proposed algorithm can improve the precision of inverse kinematics and prevent the leap of joints.

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Hovering Control of an Underwater Vehicle

Hovering Control of an Underwater Vehicle

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2022 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2022

作者： Cao, Yaozhong Song, Dalei Wang, Zhan Wang, Yu University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing100190 China Ocean University of China Department of Automation and Measurement Qingdao266100 China Zhejiang Provincial Energy Group Company Ltd Hangzhou310000 China

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

This paper aims to achieve the hovering control of an underwater vehicle with uncertain parameters based on cascade PID. First, the inner loops for each channels are designed respectively. Then, the outer loops including depth controller, horizontal position controller and yaw controller are designed. The vector transformation method are used to force the vehicle to approach the target point along approximately straight line in the horizontal plane. Simulation results demonstrate the stability and validity of the proposed method. © 2022 IEEE.

关键词： Controllers

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Kernel semi-supervised graph embedding model for multimodal and mixmodal data

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Science China(Information Sciences) 2020年第1期63卷 247-249页

作者： Qi ZHANG Rui LI Tianguang CHU School of Information Technology & Management University of International Business & Economics Key Laboratory of Machine Perception(Ministry of Education) Peking University School of Mathematical Sciences Dalian University of Technology State Key Laboratory for Turbulence and Complex Systems College of Engineering Peking University

Dear editor,Semi-supervised learning has obtained increasing interests in machine learning, because making use of both labeled and unlabeled training samples helps extracting discriminative features and meanwhile reduces the time-consuming and labor-intensive labeling burden. For extracting features upon multimodal (i.e., data of the same

关键词： Kernel semi-supervised graph embedding model for multimodal and mixmodal data

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Deep learning radiomics of multimodal ultrasound for classifying metastatic cervical lymphadenopathy into primary cancer sites: a feasibility study

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Ultraschall in der Medizin - European Journal of Ultrasound 2023年第3期45卷 305-315页

作者： Yangyang Zhu Zheling Meng Hao Wu Xiao Fan Wenhao lv Jie Tian Kun Wang Fang Nie Medical Center of Ultrasound Lanzhou University Second Hospital Lanzhou China CAS Key Laboratory of Molecular Imaging The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of the Chinese Academy of Sciences School Beijing China Gansu Province Medical Engineering Research Center for Intelligence Ultrasound Lanzhou China

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AdvDiffuser: Generating Adversarial Safety-Critical Driving Scenarios via Guided Diffusion

arXiv

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arXiv 2024年

作者： Xie, Yuting Guo, Xianda Wang, Cong Liu, Kunhua Chen, Long School of Computer Science and Engineering Sun Yat-Sen University China School of Computer Science Wuhan University China State Key Laboratory for Management and Control of Complex Systems The Institute of Automation Chinese Academy of Sciences China School of Mechanical and Automotive Engineering Qingdao University of Technology China

Safety-critical scenarios are infrequent in natural driving environments but hold significant importance for the training and testing of autonomous driving systems. The prevailing approach involves generating safety-critical scenarios automatically in simulation by introducing adversarial adjustments to natural environments. These adjustments are often tailored to specific tested systems, thereby disregarding their transferability across different systems. In this paper, we propose AdvDiffuser, an adversarial framework for generating safety-critical driving scenarios through guided diffusion. By incorporating a diffusion model to capture plausible collective behaviors of background vehicles and a lightweight guide model to effectively handle adversarial scenarios, AdvDiffuser facilitates transferability. Experimental results on the nuScenes dataset demonstrate that AdvDiffuser, trained on offline driving logs, can be applied to various tested systems with minimal warm-up episode data and outperform other existing methods in terms of realism, diversity, and adversarial performance. © 2024, CC BY.

关键词： Automatic guided vehicles

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Research Progress of Parallel Control and management

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IEEE/CAA Journal of Automatica Sinica 2020年第2期7卷 355-367页

作者： Gang Xiong Xisong Dong Hao Lu Dayong Shen State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Computer Science and Technology Beijing Institute of TechnologyBeijing 100081China College of Systems Engineering National University of Defense TechnologyChangsha 410073China

Based on ACP(artificial systems,computational experiments,and parallel execution)methodology,parallel control and management has become a popularly systematic and complete solution for the control and management of complex *** paper focuses on summarizing comprehensive review of the research literature of parallel control and management achieved in the recent years including the theoretical framework,core technologies,and the application *** future research,application directions,and suggestions are also discussed.

关键词： ACP methodology artificial systems computational experiments parallel control parallel management parallel systems

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Geometry Problem Solving Based on Counter-Factual Evolutionary Reasoning 19

Geometry Problem Solving Based on Counter-Factual Evolutiona...

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19th IEEE International Conference on Automation Science and Engineering, CASE 2023

作者： Song, Bing Xiong, Gang Shen, Zhen Zhu, Fenghua Lv, Yisheng Ye, Peijun Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Institute of Automation Chinese Academy of Sciences The Beijing Engineering Research Center of Intelligent Systems and Technology China Chinese Academy of Sciences The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Dongguan523808 China Qingdao Academy of Intelligent Industries Intelligent Manufacturing Center Qingdao266000 China

ISBN: (纸本)9798350320695

As a representative topic in natural language processing and automated theorem proving, geometry problem solving requires an abstract problem understanding and symbolic reasoning. A major challenge here is to find a feasible reasoning sequence that is consistent with given axioms and the theorems already proved. Most recent methods have exploited neural network-based techniques to automatically discover eligible solving steps. Such a kind of methods, however, is greatly impacted by the expert solutions for training. To improve the accuracy, this paper proposes a new method called counterfactual evolutionary reasoning, which uses a generative adversarial network to generate initial reasoning sequences and then introduces counterfactual reasoning to explore potential solutions. By directly exploring theorem candidates rather than the neural network selection, the new method can sufficiently extend the searching space to get a more appropriate reasoning step. Through comparative experiments on the recent proposed Geometry3k, the largest geometry problem solving dataset, our method generally achieves a higher accuracy than most previous methods, bringing an overall improvement about 4.4% compared with the transformer models. © 2023 IEEE.

关键词： Geometry

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Path Following and Collision Avoidance of a Ribbon-Fin Propelled Underwater Biomimetic Vehicle-Manipulator System

SSRN

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SSRN 2022年

作者： He, Yanbing Dong, Xiang Wang, Yu Wang, Shuo Cheng, Long School of Electrical Engineering and Automation Anhui University Hefei230601 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China

This paper addresses the problem of path following and dynamic obstacle avoidance for underwater biomimetic vehicle-manipulator system (UBVMS). Firstly, the general kinematics and dynamics models of underwater vehicles are presented;then a nonlinear model predictive control (NMPC) scheme is employed to track a reference path and collision avoidance simultaneously. Moreover, to minimize the tracking error and a higher degree of robustness, improved extended state observers are used to estimate model uncertainties and disturbances to be fed into the NMPC prediction model. On top of this, the proposed method also considers the uncertainty of the state estimator, while combining a priori estimation of the Kalman filter to reasonably predict the position of dynamic obstacles during short periods. Finally, simulations and experimental results are carried out to assess the validity of the proposed method in case of disturbances and constraints. © 2022, The Authors. All rights reserved.

关键词： Vehicles

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Muscle Synergy Analysis Based on NMF for Lower Limb Motor Function Assessment

Muscle Synergy Analysis Based on NMF for Lower Limb Motor Fu...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Xiang, Kexin Wang, Weiqun Hou, Zeng-Guang Zhang, Chutian Wang, Jiaxing Shi, Weiguo Jiao, Yuze Lin, Tianyu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The School of Intelligence University of Chinese Academy of Sciences Beijing100049 China CASIA-MUST Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology 999078 China Macau Institute of Systems Engineering Macau University of Science and Technology China The CASIAMUST Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology China

ISBN: (纸本)9781665481090

Accurate rehabilitation assessments are essential for designing effective rehabilitation methods and helping patients recover better. It's well known that commonly used scale assessment methods for neurorehabilitation suffer from the issue of subjectivity, thus investigation of objective assessment methods is very necessary. Muscle synergy analysis can be uesd to assess limb motor functions from the perspective of neuromuscular control. In this paper, a method for evaluation of human lower limb motor functions based on muscle synergy analysis is presented. Muscle synergy modules are designed using surface electromyography (sEMG) signals of the subjects' lower limbs by non-negative matrix factorizations (NMF). By comparing the cosine similarities of these synergy modules, it can be seen that muscle synergies of healthy subjects and patients are significantly different, while they are similar among healthy subjects. Therefore, a reference synergy module (RSM) is designed by averaging the muscle synergy modules for healthy subjects, and the similarities can be calculated by comparing the synergy modules for healthy subjects or patients with the RSM. In the experiment carried out in this study, average similarities of the three synergy modules for healthy subjects are respectively 0.97166, 0.87368 and 0.84932, and on the other hand, the average similarities for the three synergy modules for patients are respectively 0.59979, 0.56426 and 0.69042. Therefore, the similarities for healthy subjects are much higher than those for SCI patients, which denotes that the similarity between an individual synergy module and the RSM can be used as an objective assessing index for evaluating patients' motor function. © 2022 IEEE.

关键词： Non-negative matrix factorization

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Scenario Engineering for Autonomous Transportation: A New Stage in Open-Pit Mines

arXiv

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arXiv 2024年

作者： Teng, Siyu Li, Xuan Li, Yuchen Li, Lingxi Xuanyuan, Zhe Ai, Yunfeng Chen, Long Hong Kong Baptist University Kowloon999077 Hong Kong BNU-HKBU UIC Zhuhai China The Department of Mathematics and Theories Peng Cheng Laboratory Shenzhen518000 China Indianapolis United States Guangdong Provincial Key Laboratory IRADS BNU-HKBU UIC Zhuhai519087 China The University of Chinese Academy of Sciences Beijing100049 China The State Key Laboratory of Multimodal Artificial Intelligence Systems The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing100190 China WAYTOUS Inc. Beijing100083 China Shenzhen518107 China

In recent years, open-pit mining has seen significant advancement, the cooperative operation of various specialized machinery substantially enhancing the efficiency of mineral extraction. However, the harsh environment and complex conditions in open-pit mines present substantial challenges for the implementation of autonomous transportation systems. This research introduces a novel paradigm that integrates Scenario Engineering (SE) with autonomous transportation systems to significantly improve the trustworthiness, robustness, and efficiency in open-pit mines by incorporating the four key components of SE, including Scenario Feature Extractor, Intelligence and Index, Calibration and Certification, and Verification and Validation. This paradigm has been validated in two famous open-pit mines, the experiment results demonstrate marked improvements in robustness, trustworthiness, and efficiency. By enhancing the capacity, scalability, and diversity of autonomous transportation, this paradigm fosters the integration of SE and parallel driving and finally propels the achievement of the '6S' objectives. Copyright © 2024, The Authors. All rights reserved.

关键词： Efficiency

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