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IEEE intelligent Vehicles Symposium

作者： Yang Yi Li Hao Zhu Hao Shang Songtian Lyu Ningyi Song Wenjie School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

ISBN: (纸本)9781509048052

Large-scale intersections stamped on maps have diverse visual features for detection, while small-scale urban intersections are hard to be identified especially when GPS signals are missing. In this paper, we propose a Hidden Markov Model (HMM) based small-scale intersection detection method utilizing monocular vision. We extract visual cues of road transformations and dynamic vehicles' tracks, and then design an Intersection Scan Model to obtain the potential traversable direction of the current road, which is the primary criterion of the intersection estimation. For better performances, we take the detections of consecutive frames into consideration and finally integrate them into HMM to estimate the probabilities of intersections. Results from KITTI datasets and real-world experiments have shown the functionality of the presented approach.

关键词： Hidden Markov models Roads Global Positioning System Vehicle dynamics Semantics Image segmentation Feature extraction

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Impedance control with New Inner Torque loop for Compliant Joints and Its Performance Analysis 36

Impedance Control with New Inner Torque loop for Compliant J...

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第36届中国控制会议

作者： Yin Ke Jian Li Zonglin Huang Shuai Li Guodong Li The Bionic Robot and System Key Laboratory School of Mechatronic EngineeringBeijing Institute of Technology Key Laboratory for Intelligent Control and Decision on Complex Systems School of AutomationBeijing Institute of Technology Beijing Jingwei Hirain Technologies

ISBN: (纸本)9781538629185

For the purpose of enhancing compliance of robot joint,an impedance control strategy with new inner torque controller is *** inertia of the motor can be scaled down thanks to this new type of torque *** of different position（motor-side position 9 and link-side position q） feedback strategies are explored through theoretical deviation,simulation and static stiffness *** expressions of static stiffness under both position feedback strategies are obtained with validity verified by Simulink *** with 9 feedback strategy,static stiffness can exceed spring stiffness under q feedback strategy with high desired stiffness,which means wider variation range of static stiffness and this benefits robot applications that require wider variation range of impedance,such as rehabilitation robots and collaborative ***,several experiments with the compliant joint prototype verify the developed controllers and show the efficiency of the proposed control approach in terms of compliant behavior.

关键词： Compliant joint Impedance control Static stiffness

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Construction of Barrier in a Fishing Game with Point Capture

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IEEE Transactions on Cybernetics 2017年第6期47卷 1409-1422页

作者： Zha, Wenzhong Chen, Jie Peng, Zhihong Gu, Dongbing School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Computer Science and Electronic Engineering University of Essex ColchesterCO4 3SQ United Kingdom

This paper addresses a particular pursuit-evasion game, called as 'fishing game' where a faster evader attempts to pass the gap between two pursuers. We are concerned with the conditions under which the evader or pursuers can win the game. This is a game of kind in which an essential aspect, barrier, separates the state space into disjoint parts associated with each player's winning region. We present a method of explicit policy to construct the barrier. This method divides the fishing game into two subgames related to the included angle and the relative distances between the evader and the pursuers, respectively, and then analyzes the possibility of capture or escape for each subgame to ascertain the analytical forms of the barrier. Furthermore, we fuse the games of kind and degree by solving the optimal control strategies in the minimum time for each player when the initial state lies in their winning regions. Along with the optimal strategies, the trajectories of the players are delineated and the upper bounds of their winning times are also derived. © 2013 IEEE.

关键词： Optimal systems

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Learning ReLU networks on linearly separable data: Algorithm, optimality, and generalization

arXiv

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arXiv 2018年

作者： Wang, Gang Giannakis, Georgios B. Chen, Jie Digital Technology Center Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States State Key Lab of Intelligent Control Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Tongji University Shanghai200092 China

Neural networks with REctified Linear Unit (ReLU) activation functions (a.k.a. ReLU networks) have achieved great empirical success in various domains. Nonetheless, existing results for learning ReLU networks either pose assumptions on the underlying data distribution being e.g. Gaussian, or require the network size and/or training size to be sufficiently large. In this context, the problem of learning a two-layer ReLU network is approached in a binary classification setting, where the data are linearly separable and a hinge loss criterion is adopted. Leveraging the power of random noise perturbation, this paper presents a novel stochastic gradient descent (SGD) algorithm, which can provably train any single-hidden-layer ReLU network to attain global optimality, despite the presence of infinitely many bad local minima, maxima, and saddle points in general. This result is the first of its kind, requiring no assumptions on the data distribution, training/network size, or initialization. Convergence of the resultant iterative algorithm to a global minimum is analyzed by establishing both an upper bound and a lower bound on the number of non-zero updates to be performed. Moreover, generalization guarantees are developed for ReLU networks trained with the novel SGD leveraging classic compression bounds. These guarantees highlight a key difference (at least in the worst case) between reliably learning a ReLU network as well as a leaky ReLU network in terms of sample complexity. Numerical tests using both synthetic data and real images validate the effectiveness of the algorithm and the practical merits of the theory. Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

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Further results on cloud control systems

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Science China(Information Sciences) 2016年第7期59卷 232-236页

作者： Yuanqing XIA Yongming QIN Di-Hua ZHAI Senchun CHAI School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology

This paper is devoted to further investigating the cloud control systems(CCSs). The benefits and challenges of CCSs are provided. Both new research results of ours and some typical work made by other researchers are p... 详细信息

关键词： cloud control systems cloud computing cyber-physical systems networked control systems big data

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Analysis of security in cyber-physical systems

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Science China. Technological Sciences 2017年第12期60卷 1975-1977页

作者： Chen Jie Zhang Fan Sun Jian School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081

In recent years, cyber-physical systems (CPSs) have received much attention from both the academic world and the industrial world, which refer to a deep integration and coordination of physical and computational resources [1,2]. Typical examples of CPSs can be found in smart grids, smart transportation systems, industrial control systems, water supply systems, and so on. Furthermore, many military systems are also CPSs. The key characteristic of CPSs is the integration of computing, control and communication. The increased interconnection between the cyber and physical spaces make CPSs vulnerable to various malicious attacks. A well-known example of an attack of CPSs is the Stuxnet which infected the control system of nuclear-fuel centrifuges of Bushehr nuclear power plant in Iran. Stuxnet makes people beware of the grave consequences of a cyber-attack on a CPS. Since many national critical infrastructures are applications of CPS, ensuring security and safety of such systems is of great importance.

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Path Planning of Messenger UAV in Air-ground Coordination

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IFAC-PapersOnLine 2017年第1期50卷 8045-8051页

作者： Yulong D. Bin X. Jie C. Hao F. Yangguang Z. Guanqiang G. Lihua D. School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing 100081 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing 100081 China

This paper addresses a UAV path planning problem for a team of cooperating heterogeneous vehicles composed of one unmanned aerial vehicle (UAV) and multiple unmanned ground vehicles (UGVs). The UGVs are used as mobile actuators while the UAV serves as a messenger to achieve information sharing among the UGVs. The UAV needs to fly over each UGV periodically to collect the information and then transmit the information to the other UGVs. The UAV path planning problem with messenger mechanism is formulated as a Dynamic Dubins Traveling Salesman Problem with Neighborhood (DDTSPN). The goal of this problem is to find the shortest route enabling the UAV to deliver information to all requested UGVs. When solving this path planning problem, a decoupling strategy is introduced to sequentially determine the access sequence of UGVs for UAV and the access location of UAV in the communication neighborhood of each UGV. The effectiveness of the proposed approach is corroborated through computational experiments on several randomly generated instances. © 2017

关键词： Air-ground coordination DDTSPN Dubins path planning messenger mechanism

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RF chain reduction for MIMO systems: A hardware prototype

arXiv

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arXiv 2019年

作者： Gong, Tierui Shlezinger, Nir Ioushua, Shahar Stein Namer, Moshe Yang, Zhijia Eldar, Yonina C. State Key Lab of Robotics Key Lab of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel School of Electrical Engineering Tel Aviv University Tel Aviv Israel Faculty of Electrical Engineering Technion Haifa Israel

RF chain circuits play a major role in digital receiver architectures, allowing passband communication signals to be processed in baseband. When operating at high frequencies, these circuits tend to be costly. This increased cost imposes a major limitation on future multiple-input multiple-output (MIMO) communication technologies. A common approach to mitigate the increased cost is to utilize hybrid architectures, in which the received signal is combined in analog into a lower dimension, thus reducing the number of RF chains. In this work we present a hardware prototype implementing analog combining for RF chain reduction. The prototype consists of a specially designed configurable combining board as well as a dedicated experimental setup. Our hardware prototype allows to evaluate the effect of analog combining in MIMO systems using actual communication signals. The experimental study, which focuses on channel estimation accuracy in MIMO channels, demonstrates that using the proposed prototype, the achievable channel estimation performance is within a small gap in a statistical sense from that obtained using a costly receiver in which each antenna is connected to a dedicated RF chain. Furthermore, in the considered scenarios, this gap becomes negligible when the reduction rate, i.e., the ratio of the number of RF chains to the number of antennas, is above 62.5%. Copyright © 2019, The Authors. All rights reserved.

关键词： Channel estimation

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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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Trajectory reshaping based guidance with impact time and angle constraints

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Chinese Journal of Aeronautics 2016年第4期29卷 984-994页

作者： Zhao Yao Sheng Yongzhi Liu Xiangdong School of Automation Beijing Institute of Technology Key Laboratory for Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

This study presents a novel impact time and angle constrained guidance law for homing missiles. The guidance law is first developed with the prior-assumption of a stationary target, which is followed by the practical extension to a maneuvering target scenario. To derive the closed-form guidance law, the trajectory reshaping technique is utilized and it results in defining a specific polynomial function with two unknown coefficients. These coefficients are determined to satisfy the impact time and angle constraints as well as the zero miss distance. Furthermore, the proposed guidance law has three additional guidance gains as design parameters which make it possible to adjust the guided trajectory according to the operational conditions and missile's capability. Numerical simulations are presented to validate the effectiveness of the proposed guidance law. (C) 2016 Chinese Society of Aeronautics and Astronautics. Production and hosting by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.

关键词： Guidance Homing missiles Impact angle Impact time Trajectory reshaping

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