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IEEE International Conference on Robotics and Automation (ICRA)

作者： Haoqi Han Xiaoming Liu Yan Chen Hao Pang Xiaoqing Tang Dan Liu Qiang Huang Tatsuo Arai Beijing Advanced Innovation Center for Intelligent Robots and Systems and School of Mechatronical Engineering Key Laboratory of Biomimetic Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Department of Micro-Nano Electronics Shanghai Jiao Tong University China Center for Neuroscience and Biomedical Engineering The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In recent years, micromanipulation technology has achieved extensive applications in industry and life science. Improving the precision and bandwidth of the micromanipulator and simultaneously reducing size, weight, and cost pose significant challenges to the existing micromanipulator design and fabrication methods. Here, we propose a 3-RRS micromanipulator with an origami-inspired spherical joint based on the PC-MEMS process, aiming for miniaturization and cost-effectiveness. The spherical joint allows rotations of 140° around the x-axis approximately, 140° around the y-axis approximately, and 20° around the z-axis approximately. The micromanipulator has weights of 0.8 g, dimensions of 16 mm × 16 mm × 22 mm, and workspace of 0.7 mm 3 . The end platform of the micromanipulator can be equipped with various effectors to accomplish different kinds of tasks. Experimental results validated its high precision and bandwidth, exhibiting its potential to perform intricate micromanipulation tasks.

关键词： Industries Fabrication Costs Micromanipulators Design methodology Bandwidth Life sciences

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Visual Explanation of Object Detectors via Saliency Maps

Visual Explanation of Object Detectors via Saliency Maps

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Jin Xiao Wenrui Liu Xiaoguang Hu Hao Jiang Weipeng Wang Li Yahang State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Beihang University Beijing China The Third Academy of CASIC Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

In recent years, rapid progress of deep learning has resulted in object detection algorithms based on deep neural networks nearly completely replacing traditional methods. This shift has led to significant improvements in both accuracy and speed of object detection. However, deep neural networks that support decision-making inobject detection are complex black boxes with hidden internal logic and operations. This lack of transparency results in deep learning models being unexplainable, which limits their practical deployment. In this paper, we analyze the current state and future trends of interpretable technology in object detection and propose an effective object detection interpretable algorithm. This algorithm aims to explain the underlying logic of AI decision-making and provide support for the high performance and credibility of object detection algorithms based on deep neural networks through quantitative evaluation indicators.

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Non-proteolytic ubiquitination of HBx controls HBV replication

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Virologica Sinica 2024年第2期39卷 338-342页

作者： Xiangpeng Sheng Yi Yang Min Zhu Linlin Zhou Fang Zhu Yuanfei Zhu Siying Dong Hui Kong Honghua Wang Ji Jiang Mingyue Wan Mingyang Feng Qiang Deng Yumin Xu Qing You Ronggui Hu State Key Laboratory for Animal Disease Control and Prevention Harbin Veterinary Research InstituteChinese Academy of Agricultural SciencesHarbin 150069China State Key Laboratory of Molecular Biology Shanghai Institute of Biochemistry and Cell BiologyCenter for Excellence in Molecular Cell ScienceChinese Academy of SciencesShanghai 200031China Key Laboratory of Systems Health Science of Zhejiang Province School of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China Department of Thoracic Surgery Ruijin HospitalShanghai Jiaotong University School of MedicineShanghai 200025China Shanghai Key Laboratory of Plant Molecular Sciences College of Life SciencesShanghai Normal UniversityShanghai 200234China Department of Pathogenic Biology West China School of Basic Medical Sciences&Forensic MedicineSichuan UniversityChengdu 610041China School of Medicine Guizhou UniversityGuiyang 550025China Key Laboratory of Medical Molecular Virology(MOE&MOH) School of Basic Medical SciencesFudan UniversityShanghai 200032China Department of Hospital Infection Management Department of Infectious DiseasesRuijin HospitalShanghai Jiao Tong University School of MedicineShanghai 200025China School of Biomedical Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Dear Editor,Although effective vaccines and antiviral therapies are available,hepatitis B virus(HBV)infection is still a serious global health *** HBV infection remains the principal cause of liver cirrhosis and hepatocellular carcinoma(HCC).HBV is a small DNA virus,owning a~3.2 kb genome that encodes several proteins:viral DNA polymerase,core antigen(HBcAg),E antigen(HBeAg),three surface antigens(PreS1/PreS2/HBsAg),and a regulatory X protein(HBx)(Lamontagne et al.,2016).X protein,named for its lack of homology with any known proteins,is a 154 aa protein that plays an essential role in HBV biology and regulates the development of HCC(Yang et al.,2022).Although previous studies have strongly expanded our understanding of HBx,the regulation of HBx is not completely elucidated.

关键词： infection cirrhosis

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Immobilizing ultrafine bimetallic PtAg alloy onto uniform MnO_(2) microsphere as a highly active catalyst for CO oxidation

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Chinese Chemical Letters 2021年第6期32卷 2057-2060页

作者： Shengpeng Mo Peng Peng Yinchang Pei Taiming Shen Qinglin Xie Mingli Fu Yunfa Chen Daiqi Ye College of Environment Science and Engineering Guilin University of TechnologyGuilin 541004China School of Environment and Energy South China University of TechnologyGuangzhou 510006China Guangxi Key Laboratory of Theory and Technology for Environmental Pollution Control Guilin University of TechnologyGuilin 541004China State Key Laboratory of Multi-Phase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China

Herein,a facile glycol reduction route is successful employed to synthesize bimetallic Pt Ag alloys with homogeneous distribution of sizes and *** studies reveal that the ultrafine Pt Ag alloys with well-defined sizes from around 3.3 nm to 5.8 nm are immobilized onto MnO_(2)microsphere,which remarkably enhances the catalytic performances for CO ***,quasi in-situ X-ray photoelectron spectroscopy(XPS)result reveals that both Mn and Pt ions on the surface of catalysts would realize alternating reduction-oxidation by CO and O_(2)molecules,and the oxygen vacancy sites could be replenished and excited by gas-phase O_(2).

关键词： Bimetallic alloys PtAg NPs MnO_(2) Quasi in-situ XPS CO oxidation

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Mechanical,corrosion and magnetic behavior of a CoFeMn_(1.2)NiGa_(0.8) high entropy alloy

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Journal of Materials Science & Technology 2021年第14期73卷 139-144页

作者： Xiaoming Sun Lingzhong Du Hao Lan Jingyi Cui Liang Wang Runguang Li Zhiang Liu Junpeng Liu Weigang Zhang State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing100190China Innovation Academy for Green Manufacture Chinese Academy of SciencesBeijing100190China School of Materials Science and Engineering Beijing Institute of TechnologyBeijing100081China X-ray Science Division Argonne National LaboratoryArgonneIllinois60439USA Experimental Teaching and Equipment Management Center Qufu Normal UniversityShandong273165China State Key Laboratory of Nonlinear Mechanics Institute of MechanicsChinese Academy of SciencesBeijing100190China

In this study,a magnetic high entropy alloy(HEA)of CoFeMn_(1.2)NiGa_(0.8)was designed and prepared by arc melting in order to investigate its mechanical,corrosion and magnetic *** results show that the alloy mainly possesses body-centered cubic(BCC)phase and face-centered cubic(FCC)phase.A high compressive strength of 1450 MPa,a strain of 18.5%and a relatively low yield strength of 303MPa in as-cast condition at room temperature can be achieved in the present ***-situ high-energy X-ray diffraction technique was employed to reveal the deformation mechanism of Co Fe Mn_(1.2)Ni Ga_(0.8)under uniaxial compression and the results show that the competition between BCC phase and FCC phase plays a significant role during the compressive *** corrosion behavior of Co Fe Mn_(1.2)Ni Ga_(0.8)was investigated in 3.5 wt%Na Cl solution and it turned out that the alloy possessed good corrosion *** last,the magnetic behavior of the Co Fe Mn_(1.2)Ni Ga_(0.8)alloy was studied and it can present a high saturation magnetization of 94.5 emu/g and a coercivity of 26.4 Oe at 4 *** work indicates that the present Co Fe Mn_(1.2)Ni Ga_(0.8)HEA has promising applications as future magnetic functional materials.

关键词： High entropy alloys High-energy X-ray diffraction Compressive property Corrosion resistance Magnetic behavior

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Conservative-Progressive Collaborative Learning for Semi-supervised Semantic Segmentation

arXiv

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arXiv 2022年

作者： Fan, Siqi Zhu, Fenghua Feng, Zunlei Lv, Yisheng Song, Mingli Wang, Fei-Yue The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Tsinghua University Beijing China The College of Computer Science and Technology Zhejiang University Hangzhou China

Pseudo supervision is regarded as the core idea in semi-supervised learning for semantic segmentation, and there is always a tradeoff between utilizing only the high-quality pseudo labels and leveraging all the pseudo labels. Addressing that, we propose a novel learning approach, called Conservative-Progressive Collaborative Learning (CPCL), among which two predictive networks are trained in parallel, and the pseudo supervision is implemented based on both the agreement and disagreement of the two predictions. One network seeks common ground via intersection supervision and is supervised by the high-quality labels to ensure a more reliable supervision, while the other network reserves differences via union supervision and is supervised by all the pseudo labels to keep exploring with curiosity. Thus, the collaboration of conservative evolution and progressive exploration can be achieved. To reduce the influences of the suspicious pseudo labels, the loss is dynamic re-weighted according to the prediction confidence. Extensive experiments demonstrate that CPCL achieves state-of-the-art performance for semi-supervised semantic segmentation. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Path Planning of Mobile Robot Based on an Improved Genetic Algorithm

Path Planning of Mobile Robot Based on an Improved Genetic A...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Zenghua Chen Gang Xiong Sheng Liu Zhen Shen Yue Li State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China School of Automobile Chang'an University Xi'an China

ISBN: (数字)9781665492270

ISBN: (纸本)9781665492287

In order to solve the problem of premature convergence of the basic genetic algorithm when planning the robot running path, the basic genetic algorithm is improved and optimized. Different population initialization methods are used to initialize multiple populations randomly, so as to improve the diversity of populations; Improve the adaptive strategy and elite strategy of crossover and mutation operators to improve the convergence speed of the algorithm; Add the path tortuosity as the planning index in the fitness function to make the planned path smoother, and add constraints to the model to avoid obstacles; Finally, through the transformation of the coding paradigm of the above improved genetic algorithm, it can run on Flink distributed cluster to obtain faster solution speed, so as to meet the efficiency requirements of path planning in large-scale robot cluster system. The optimized algorithm is compared with the basic genetic algorithm. The simulation results show that the improved algorithm is efficient in robot path planning.

关键词： Sociology Clustering algorithms Path planning Planning Trajectory Statistics Collision avoidance

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Modified Deep Deterministic Policy Gradient Based Optimal Speed Tracking Strategy for PMSMs

Modified Deep Deterministic Policy Gradient Based Optimal Sp...

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Data Driven control and Learning systems (DDCLS)

作者： Zhong-Xin Fan Lintao Tang Shihua Li Rongjie Liu School of Automation Southeast University Nanjing P. R. China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing P. R. China Department of Statistics Florida State University Tallahassee FL USA

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

Achieving optimal speed regulation for permanent magnet synchronous motors (PMSMs) remains a challenging task, particularly in selecting the most suitable controller to meet desired objectives. This paper considers the optimal speed tracking problem of PMSMs. We employ a reinforcement learning algorithm to obtain optimal controller with a linear form. The reinforcement learning approach incorporates a critic-actor network structure, which approximates the value function and optimal control, respectively. Specifically, a weight updating method for the critic network is introduced, where the update of the actor network is guided by the critic network. Through data collection and neural network training, dynamic acquisition of the optimal controller gain is achieved. In addition, a novel activation function is implemented in the network, leading to improved control performance concerning dataset size and reduced training time. At final, a real-world PMSM application is presented along with comparisons to demonstrate effectiveness. The desire idea of resulting optimal controllers is not only applicable to linear systems but also capable of approximating arbitrary nonlinear optimal controllers, thus offering practical engineering versatility.

关键词： Training Linear systems Learning systems Neural networks Optimal control Reinforcement learning Data collection

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A Hierarchical Deep Reinforcement Learning Framework for 6-DOF UCAV Air-to-Air Combat

arXiv

引用

arXiv 2022年

作者： Chai, Jiajun Chen, Wenzhang Zhu, Yuanheng Yao, Zong-Xin Zhao, Dongbin State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China China

Unmanned combat air vehicle (UCAV) combat is a challenging scenario with continuous action space. In this paper, we propose a general hierarchical framework to resolve the within-vision-range (WVR) air-to-air combat problem under 6 dimensions of degree (6-DOF) dynamics. The core idea is to divide the whole decision process into two loops and use reinforcement learning (RL) to solve them separately. The outer loop takes into account the current combat situation and decides the expected macro behavior of the aircraft according to a combat strategy. Then the inner loop tracks the macro behavior with a flight controller by calculating the actual input signals for the aircraft. We design the Markov decision process for both the outer loop strategy and inner loop controller, and train them by proximal policy optimization (PPO) algorithm. For the inner loop controller, we design an effective reward function to accurately track various macro behavior. For the outer loop strategy, we further adopt a fictitious self-play mechanism to improve the combat performance by constantly combating against the historical strategies. Experiment results show that the inner loop controller can achieve better tracking performance than fine-tuned PID controller, and the outer loop strategy can perform complex maneuvers to get higher and higher winning rate, with the generation evolves. Copyright © 2022, The Authors. All rights reserved.

关键词： Reinforcement learning

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Solving Environment Economic Power Dispatch Problemroblems by Multi-objective Modified Seagull Optimization Algori Algorithm with Novel Constraint Treatments

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IAENG International Journal of Applied Mathematics 2023年第1期53卷

作者： Chen, Gonggui Tan, Tao Xiang, Wei Guan, Zhenqi Tan, Hao Yu, Jianbo Long, Hongyu Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing University of Posts and Telecommunications Chongqing400065 China Economic and Technology Research Institute State Grid Chongqing Electric Power Company Chongqing401120 China Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China

In this paper, a multi-objective modified seagull optimization algorithm (MOMSOA) is proposed to handle multi-objective environmental economic power dispatch (EED) problems. The algorithm utilizes logistic map to randomize the parameter u, which increases the diversity of the algorithm and speeds up the convergence rate. Besides, the mutation operator is combined to enlarge the range of the search and to avoid falling into the local optimum. The exploration as well as exploitation capabilities for MOSOA are balanced by non-linearizing the original linear parameter A through a cosine dynamic variation strategy. Furthermore, with the assistance of a unique constraint handling approach and non-inferior sorting, MOMSOA can obtain a set of uniform Pareto optimal solution (POS). In order to verify the effectiveness of MOMSOA, experiments were conducted on diverse test systems including IEEE30-Bus, IEEE57-Bus and IEEE118-Bus test systems. During the experimental process, MOSOA and MOPSO/MODE are compared with MOMSOA. Eight trials were conducted, and optimized objective functions include fuel cost, fuel cost with valve point effect, power loss and pollution emission. The results of experiments demonstrate that the proposed MOMSOA can obtain more uniform Pareto fronts (PFs) and optimal best compromise solution (BCS). Finally, two metrics that measure the performance of multi-objective algorithms, SP and HV, are employed to evaluate the results of each algorithm, and the results reveal that solutions obtained by MOMSOA are the most uniform, with the broadest diversity and the best convergence. © 2023, IAENG International Journal of Applied Mathematics. All Rights Reserved.

关键词： Constraint handling

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