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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Yiwen Liu Qingqing Ji Quankai Zheng Huaiyu Wu Zhihai Wang Gang Xiong Faculty of Information The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing University of Technology Beijing China University of Chinese Academy of Sciences Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Economics Finance and Management University of Bristol Bristol UK The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Information Beijing University of Technology Beijing China

As a new technology with subversive significance in the Internet field, blockchain has received extensive attention from research and applications sector in recent years. Its decentralized structure and unchangeable data nature have a wide application prospect in Internet transactions. However, it is difficult to implement supervision in a partially decentralized system. Therefore, a blockchain system with a single or a few central nodes has emerged during the development of blockchain. For such special partially decentralized blockchain systems, more scientific development is needed. This paper takes X insurance trading chain as an example to study this partially decentralized blockchain system, to make a more scientific security assessment of this kind of system, and put forward corresponding countermeasures to improve the security of this kind of system.

关键词： Blockchain Insurance Security Distributed databases Online banking Contracts

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An image processing method for green apple lesion detection in natural environment based on GA-BPNN and SVM 15

An image processing method for green apple lesion detection ...

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15th IEEE International Conference on Mechatronics and automation, ICMA 2018

作者： Tian, Yunong Li, En Yang, Lei Liang, Zize State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781538660720

The technologies of information processing, especially the image processing, are important technical means to realize intelligent management and control of modern orchard. In order to realize the intelligentization of orchard production, the orchard image database, especially the lesion image database needs to be set up. Because of the uneven illumination and the complex background under the natural light condition, traditional image segmentation methods cannot solve the adaptive threshold issue during the lesion image processing of green apples. This paper proposes an image processing method based on a BP neural network updated by genetic algorithm (GA-BPNN) and support vector machine (SVM) to realize lesion image processing of green apples in orchard. With this method, apple images can be processed in batch and the lesion image database can be consummated automatically. Furthermore, the recognition of the diseased apple is realized. The experimental results show that the proposed method can obtain green apple segmentation and lesion detection with good efficiency and robustness in complex natural orchard environment. © 2018 IEEE.

关键词： Support vector machines

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A vision-based robotic grasping approach under the disturbance of obstacles 15

A vision-based robotic grasping approach under the disturban...

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15th IEEE International Conference on Mechatronics and automation, ICMA 2018

作者： Zhao, Xionglei Cao, Zhiqiang Jia, Qun Pang, Lei Yu, Yingying Tan, Min State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781538660720

This paper presents a vision-based robotic grasping approach with complex obstacles environments. A deep learning-based object detection algorithm is used to detect object in the image and obtain the object's category and position. Then the Euclidean cluster extraction algorithm is adopted to segment scenes composed of 3D point clouds to obtain the positions and size of obstacles. According to the acquired information of the object and obstacles, one can judge whether the object can be directly grasped. If there is no direct solution, the obstacles that interfere with the grasping shall be firstly moved to other positions, then the object is grasped. These new positions of interference obstacles are selected based on artificial potential field. The experimental results on the Kinova MICO2 arm demonstrate that the approach can effectively achieve the grasping of target object even with severe interference from obstacles. © 2018 IEEE.

关键词： Object detection

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Foundation models and intelligent decision-making: Progress, challenges, and perspectives

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Innovation 2025年第6期6卷 100948页

作者： Huang, Jincai Xu, Yongjun Wang, Qi Wang, Qi [Cheems] Liang, Xingxing Wang, Fei Zhang, Zhao Wei, Wei Zhang, Boxuan Huang, Libo Chang, Jingru Ma, Liantao Ma, Ting Liang, Yuxuan Zhang, Jie Guo, Jian Jiang, Xuhui Fan, Xinxin An, Zhulin Li, Tingting Li, Xuefei Shao, Zezhi Qian, Tangwen Sun, Tao Diao, Boyu Yang, Chuanguang Yu, Chenqing Wu, Yiqing Li, Mengxian Zhang, Haifeng Zeng, Yongcheng Zhang, Zhicheng Zhu, Zhengqiu Lv, Yiqin Li, Aming Chen, Xu An, Bo Xiao, Wei Bai, Chenguang Mao, Yuxing Yin, Zhigang Gui, Sheng Su, Wentao Zhu, Yinghao Gao, Junyi He, Xinyu Li, Yizhou Jin, Guangyin Ao, Xiang Zhai, Xuehao Tan, Haoran Yun, Lijun Shi, Hongquan Li, Jun Fan, Changjun Huang, Kuihua Harrison, Ewen Leung, Victor C.M. Qiu, Sihang Dong, Yanjie Zheng, Xiaolong Wang, Gang Zheng, Yu Wang, Yuanzhuo Guo, Jiafeng Wang, Lizhe Cheng, Xueqi Wang, Yaonan Yang, Shanlin Fu, Mengyin Fei, Aiguo Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Department of Automation Tsinghua University Beijing100084 China Huazhong University of Science and Technology Wuhan430074 China School of Automation Beijing Institute of Technology Beijing100081 China School of Information Science and Engineering Dalian Polytechnic University Dalian116034 China National Engineering Research Center for Software Engineering Peking University Beijing100871 China Department of Oral Implantology Peking University School and Hospital of Stomatology Beijing100081 China Guangzhou511453 China College of Information and Electrical Engineering China Agricultural University Beijing100083 China IDEA Research International Digital Economy Academy Shenzhen518057 China Institute of Automation Chinese Academy of Sciences Beijing100190 China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China College of Science National University of Defense Technology Changsha410073 China Center for Systems and Control College of Engineering Peking University Beijing100871 China Gaoling School of Artificial Intelligence Renmin University of China Beijing100872 China College of Systems Engineering National University of Defense Technology Changsha410073 China Laboratory for Big Data and Decision National University of Defense Technology Changsha410073 China College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore School of Electrical Engineering Chongqing University Chongqing400044 China Department of Mathematics The University of Hong Kong Hong Kong SAR999077 China School of Food Science and Technology Dalian Polytechnic University Dalian116034 China Centre for Medical Informatics University of Edinburgh EdinburghEH16 4UX United Kingdom Department of Stomatology Peking Union Medical College Hospital Chinese Academ

Intelligent decision-making (IDM) is a cornerstone of artificial intelligence (AI) designed to automate or augment decision processes. Modern IDM paradigms integrate advanced frameworks to enable intelligent agents to make effective and adaptive choices and decompose complex tasks into manageable steps, such as AI agents and high-level reinforcement learning. Recent advances in multimodal foundation-based approaches unify diverse input modalities—such as vision, language, and sensory data—into a cohesive decision-making process. Foundation models (FMs) have become pivotal in science and industry, transforming decision-making and research capabilities. Their large-scale, multimodal data-processing abilities foster adaptability and interdisciplinary breakthroughs across fields such as healthcare, life sciences, and education. This survey examines IDM's evolution, advanced paradigms with FMs and their transformative impact on decision-making across diverse scientific and industrial domains, highlighting the challenges and opportunities in building efficient, adaptive, and ethical decision systems. © 2025 The Authors

关键词： Reinforcement learning

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Compare contact model-based control and contact model-free learning: A survey of robotic peg-in-hole assembly strategies

arXiv

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arXiv 2019年

作者： Xu, Jing Hou, Zhimin Liu, Zhi Qiao, Hong State Key Laboratory of Tribology Beijing Key Laboratory of Precision/Ultra-Precision Manufacturing Equipment Control Department of Mechanical Engineering Tsinghua University Beijing100084 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

In this paper, we present an overview of robotic peg-in-hole assembly and analyze two main strategies: Contact model-based and contact model-free strategies. More specifically, we first introduce the contact model control approaches, including contact state recognition and compliant control two steps. Additionally, we focus on a comprehensive analysis of the whole robotic assembly system. Second, without the contact state recognition process, we decompose the contact modelfree learning algorithms into two main subfields: Learning from demonstrations and learning from environments (mainly based on reinforcement learning). For each subfield, we survey the landmark studies and ongoing research to compare the different categories. We hope to strengthen the relation between these two research communities by revealing the underlying links. Ultimately, the remaining challenges and open questions in the field of robotic peg-in-hole assembly community are discussed. The promising directions and potential future work are also considered. Copyright © 2019, The Authors. All rights reserved.

关键词： Reinforcement learning

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A survey on fabrication,control,and hydrodynamic function of biomimetic robotic fish

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Science China(Technological Sciences) 2017年第9期60卷 1365-1380页

作者： YU JunZhi WEN Li REN ZiYu State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Mechanical Engineering and Automation Beihang University

Understanding and replicating the locomotion principles offish are fundamental in the development of artificial fishlike robotic systems,termed robotic *** paper has two objectives:(1) to review biological clues on biomechanics and hydrodynamic flow control offish swimming and(2) to summarize design and control methods for efficient and stable swimming in robotic *** review of state-of-the-art research and future-oriented new directions indicates that fish-inspired biology and engineering interact in mutually beneficial *** strong interaction offers an important insight into the design and control of novel fish-inspired robots that addresses the challenge of environmental uncertainty and competing objectives;in addition,it also facilitates refinement of biological knowledge and robotic strategies for effective and efficient swimming.

关键词： fish swimming robots robotic fish hydrodynamics motion control

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Research and Application of Industrial Equipment management Service System Based on Cloud-Edge Collaboration

Research and Application of Industrial Equipment Management ...

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Chinese automation Congress (CAC)

作者： Hua Zhang Shichao Chen Ping Zou Gang Xiong Hongxia Zhao Yicun Zhang Platform Research and Development Department Beijing Aerospace Smart Manufacturing Technology Development Co.Ltd Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Macau University of Science and Technology Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Product Department Zhejiang Hanshow Technology Co.Ltd Beijing China

With the integration development of Internet of Things, edge computing, cloud computing and artificial intelligence, the computing paradigm centered on traditional cloud computing has begun to integrate the edge computing paradigm, forming an industrial Internet of Things revolution based on Cloud-Edge collaboration. It not only can improve the response speed of industrial field system and reduce the load pressure of network bandwidth caused by data transmission, but also can realize the refined management of industrial devices and the deep mining of industrial data by on the cloud platform. In short, the cloud platform and the edge platform can play their respective advantages and continue to promote the industrial Internet of Things to the intellectualized development. In this paper, it started from the system architecture, and an industrial equipment management service system based on Cloud-Edge collaboration was discussed, including the design of equipment management service cloud platform and edge intelligent gateway in detail. The central airconditioning energy consumption monitoring and optimization application based on INDICS platform and SMART IOT edge intelligent gateway were introduced, to verify system availability.

关键词： Cloud computing Collaboration Logic gates Data models Memory Edge computing Internet of Things

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An efficient 3D pedestrian detector with calibrated RGB camera and 3D LiDAR

An efficient 3D pedestrian detector with calibrated RGB came...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Pang, Lei Cao, Zhiqiang Yu, Junzhi Liang, Shuang Chen, Xuechao Zhang, Weimin State Key Lab Management and Control for Complex Systems Institute of Automation CAS Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Dept. Mech. Eng. Sci. BIC-ESAT College of Engineering Peking University Beijing100871 China BAICIRS Beijing100081 China Intell. Robot. Inst. Beijing Inst. Technol. Beijing100081 China

ISBN: (纸本)9781728163215

Pedestrian detection plays an important role in the environmental perception and autonomous navigation for robotics, which provides critical information for the safe operation in complex environments. In this paper, a 3D pedestrian detector with calibrated LiDAR and RGB Camera is proposed, which takes full advantage of the precise range information of 3D LiDAR scanner and semantic information acquired from RGB image. The proposed approach integrates the segmented object clusters of point cloud and 2D bounding boxes generated by a visual object detector. The point cloud is segmented by a three-step segmentation approach, which can segment point cloud with both high precision and high efficiency. By fusion multi-sensor information in the image domain, the proposed approach provides 3D information of pedestrians in both LiDAR and camera coordinate systems. Experiments was conducted to evaluate the performance of the proposed approach. © 2019 IEEE.

关键词： Cameras

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Optimization of Grouping Evacuation Strategy in High-rise Building Fires Based on Graph Theory and Computational Experiments

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IEEE/CAA Journal of Automatica Sinica 2018年第6期5卷 1104-1112页

作者： Yuling Hu Xiwei Liu School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing 100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing 100044China State Key Laboratory fo Management and Control for Complex Systems Institute of Automation Chinese Academy of SciencesBeijing 100190China Qingdao Academy of Intelligent Industries Qingdao 266109China

It is difficult to rescue people from outside, and emergency evacuation is still a main measure to decrease casualties in high-rise building fires. To improve evacuation efficiency, a valid and easily manipulated grouping evacuation strategy is proposed. Occupants escape in groups according to the shortest evacuation route is determined by graph theory. In order to evaluate and find the optimal grouping, computational experiments are performed to design and simulate the evacuation processes. A case study shown the application in detail and quantitative research conclusions is obtained. The thoughts and approaches of this study can be used to guide actual high-rise building evacuation processes in future.

关键词： Computational experiments grouping evacuation graph theory high-rise building fire management strategies

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Accelerating minibatch stochastic gradient descent using typicality sampling

arXiv

引用

arXiv 2019年

作者： Peng, Xinyu Li, Li Wang, Fei-Yue Department of Automation Tsinghua University Beijing100084 China Department of Automation Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing100084 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100080

Machine learning, especially deep neural networks, has been rapidly developed in fields including computer vision, speech recognition and reinforcement learning. Although Minibatch SGD is one of the most popular stochastic optimization method in training deep networks, it shows a slow convergence rate due to the large noise in gradient approximation. In this paper, we attempt to remedy this problem by building more efficient batch selection method based on typicality sampling, which reduces error of gradient estimation in conventional Minibatch SGD. We analyze convergence rate of the resulting typical batch SGD algorithm, and compare convergence properties between Minibatch SGD and the algorithm. Experimental results demonstrate that our batch selection scheme works well and more complex Minibatch SGD variants can benefit from the proposed batch selection strategy. Copyright © 2019, The Authors. All rights reserved.

关键词： Reinforcement learning

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