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arXiv 2024年

作者： Yu, Jingru Yu, Yi Wang, Xuhong Lin, Yilun Yang, Manzhi Qiao, Yu Wang, Fei-Yue Shanghai Artificial Intelligence Laboratory Shanghai200240 China The Macau Institute of Systems Engineering Macau University of Science and Technology China Eversec Technology Company Ltd. Beijing100080 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

Social engineering (SE) attacks remain a significant threat to both individuals and organizations. The advancement of Artificial Intelligence (AI), including diffusion models and large language models (LLMs), has potentially intensified these threats by enabling more personalized and convincing attacks. This survey paper categorizes SE attack mechanisms, analyzes their evolution, and explores methods for measuring these threats. It highlights the challenges in raising awareness about the risks of AI-enhanced SE attacks and offers insights into developing proactive and adaptable defense strategies. Additionally, we introduce a categorization of the evolving nature of AI-powered social engineering attacks into"3E phases": Enlarging, wherein the magnitude of attacks expands through the leverage of digital media;Enriching, introducing novel attack vectors and techniques;and Emerging, signifying the advent of novel threats and methods. Moreover, we emphasize the necessity for a robust framework to assess the risk of AI-powered SE attacks. By identifying and addressing gaps in existing research, we aim to guide future studies and encourage the development of more effective defenses against the growing threat of AI-powered social engineering. Copyright © 2024, The Authors. All rights reserved.

关键词： Artificial intelligence

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Real-time terrain assessment and Bayesian-based path planning for off-road navigation

Real-time terrain assessment and Bayesian-based path plannin...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Tianwei Niu Shuwei Yu Liang Wang Haoyu Yuan Shoukun Wang Junzheng Wang Localization and Motion Planning School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System School of Automation Beijing Institute of Technology Beijing China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In the context of unstructured and unknown environment, the autonomous navigation still faces many challenges, such as assessing rough terrain and deciding how to safely navigate complex terrain. In this work, we propose a robust and practical off-road navigation framework that has been successfully deployed on a vibroseis truck for land exploration. First, in degraded wild scenes, a tightly coupled lidar-GNSS-inertial fusion odometry and mapping framework is adopted to construct a local point cloud map around the vehicle in real-time and provide precise localization. Then, based on amplitude-frequency characteristic analysis and point cloud PCA, a multi-layer terrain assessment map containing terrain roughness, obstacles and slope information is obtained. Finally, combining Gaussian distribution based adaptive sampler and Bayesian sequentially updated proposal distribution, a local graph is efficiently built to obtain multiple path solutions under constrained conditions. Both simulations and field experiments show that the proposed navigation framework can decide how to travel on a flat road even in harsh terrain conditions, naturally suppressing frequent attitude angle changes and preventing vehicle accidents.

关键词： Point cloud compression Location awareness Adaptation models Navigation Roads Gaussian distribution Real-time systems Bayes methods Proposals Principal component analysis

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PiAGI: The Concept, Mechanism and Framework

PiAGI: The Concept, Mechanism and Framework

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

作者： Qiang Li Zhuoya Ju Lili Fan Xin Liu Wenhua Liu Feiyue Wang Scientific and Technological Innovation Center Beijing China The School of Automation Beijing Institute of Technology Beijing China School of Big Data & Cyber Security China University of Petroleum Qingdao China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

As social production and living spaces gradually expand from the physical and information domains to the cognitive and social domains, this article addresses the new changes brought about by these expansions. Starting from the new impact of era of intelligent connectivity on social cognitive management, it analyzes the urgent need to enhance social cognitive management capabilities centered on cognitive decision-making, identifying the core key as Adversarial Generated Intelligence (AGI). It delves into the conceptual characteristics, operating mechanisms, and winning strategies of AGI, identifies the new challenges it faces, and proposes a Parallel Intelligence empowering AGI (PiAGI) system architecture through the empowerment of parallel intelligence. This provides theoretical support for improving social cognitive management capabilities centered on cognitive decision-making.

关键词： Decision making systems architecture Production Digital twins Faces

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The DAO to Social Transportation: Towards Smart Mobility in Cyber-Physical-Social Space

The DAO to Social Transportation: Towards Smart Mobility in ...

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IEEE International Conference on systems, Man and Cybernetics

作者： Yuanyuan Chen Yisheng Lv Fei-Yue Wang State Key Lab. of Multimodal Artificial Intelligence Systems Chinese Academy of Sciences Institute of Automation Beijing China State Key Lab. for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China

The rapid advancement of intelligence and connectivity technology (ICT) has enhanced the efficiency and safety of intelligent transportation systems (ITS). However, this also increases the complexity of the transportation systems, especially the social complexity, and poses new challenges for their management. This paper discusses the emergence of social transportation, as part of natural evolutionary adaptation to new traffic conditions and technology, which is a paradigm shift from engineering-centered technical systems to society-centered ecosystems. In social transportation systems, all participants including administrators, individual travelers and other stakeholders play a more proactive role in the operation and management of transportation systems. Therefore, we propose to employ a decen-tralized autonomous organization (DAO) as a model for the social transportation system that allows participants to collaborate and coordinate without relying on a central authority. To meet the challenges brought by this transition, we propose to apply ACP-based parallel system theory to restructure the methodology of transportation management. Finally, we present a case study of personal carbon trading system where economic incentives are used to manage traffic demand, affecting others' travel behaviors, and reduce carbon emissions. In the conclusive remarks, we provide our visions and future directions of social transportation systems.

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An intelligent maritime scene frame prediction based on digital twins technology 1

An intelligent maritime scene frame prediction based on digi...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Guo, Zhong-Zheng Wang, Kai Qin, Jiang-Yi Li, Xian-Bin Ran, De-Chao Shen, Yu Unmanned Systems Research Center National Innovation Institute of Defense Technology Academy of Military Science Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China

ISBN: (纸本)9781665433372

This paper proposes a scene frame prediction system based on digital twin technology. The system is mainly composed of an unmanned perception module, a communication link module, a command center module that provides intelligent computing services, and an interaction and visualization module for human operators. These modules together constitute a system for predicting and recovery the time-series matrix composed of scene frames and object frames. At the same time, in view of the current problems of lack of real-time information and long response time in the maritime search and rescue (SAR) field, this paper instantiates the above system to improve the existing SAR system. Satellites and unmanned vehicles perceive part of the scene data of the real cyber-physical system in real-time and divide them into multiple frames according to the timestamps. In addition, this paper also proposes an environmental graph-attention network (Env-GAT) to achieve efficient and reliable frame predicting. Finally, this paper verifies that the performance of the spatiotemporal attention graph network model has reached the optimal level through computational experiments. © 2021 IEEE.

关键词： Forecasting

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Hydrodynamic Analysis and Verification of an Innovative Whale Shark-like Underwater Glider

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Journal of Bionic Engineering 2020年第1期17卷 123-133页

作者： Huijie Dong Zhengxing Wu Min Tan Junzhi Yu State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceBIC-ESATCollege of EngineeringPeking UniversityBeijing 100871China

This paper presents an innovative design for a biomimetic whale shark-like underwater glider aiming at the combination of high maneuverability and long *** a hybrid of the underwater glider and the robotic fish,its pectoral fins and tail can serve as not only the external control surfaces for attitude regulation during gliding but also the propellers for agile fish-like swimming *** verify the gliding capability of the whale shark-like glider and prepare for future dynamic analysis,the hydrodynamic coefficients,including drag,lift,sliding force,and corresponding moments are estimated through computational fluid dynamics *** addition,the hydrodynamic analyses of the proposed glider and an equivalent conventional glider during steady gliding motion are executed for *** experiments are performed to verify the downward gliding *** results reveal that the whale shark-like glider has less drag as well as higher lift-to-drag ratio and a markable gliding capability in *** may offer important inspiration for improving the gliding efficiency and performance of an underwater glider in biomimetic shape design.

关键词： biomimetic robot CFD hydrodynamic analysis underwater glider

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Visuotactile Feedback Parallel Gripper for Robotic Adaptive Grasping

Visuotactile Feedback Parallel Gripper for Robotic Adaptive ...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Zhang, Boyue Cui, Shaowei Zhang, Chaofan Hu, Jingyi Wang, Shuo School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Institute of Automation Chinese Academy of Sciences Beijing100190 China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing100190 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

ISBN: (纸本)9781665481090

In robot grasp and dexterous manipulation tasks, tactile sensing is important for the control adjustment of the manipulator. In this paper, we present a novel low-cost parallel gripper with high-resolution tactile sensing, named the GelStereo Gripper. Furthermore, an adaptive grasp strategy is proposed to endow the gripper with tactile-feedback grasp stability-maintaining ability. We install the gripper on our robot platform and conduct various grasp experiments by utilizing proposed control methods. Experimental results verify the reliability of the GelStereo gripper and also prove the effectiveness of the proposed strategy for experimental objects with different features. © 2022 IEEE.

关键词： Grippers

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GPIO Based Iterative Learning control for Manipulators with Time-Varying Disturbances 42

GPIO Based Iterative Learning Control for Manipulators with ...

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42nd Chinese control Conference, CCC 2023

作者： Lu, Huangyuwei Wang, Zuo Sun, Jiankun Xiao, Xi Li, Shihua School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Shenzhen Research Institute Southeast University Shenzhen518063 China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration Nanjing211106 China

ISBN: (纸本)9789887581543

To improve the disturbance rejection ability and repetitive tracking accuracy of manipulators, a composite iterative learning control (ILC) scheme via generalized proportional integral observer (GPIO) is proposed. A high-order polynomial is first employed to model the time-varying disturbances that include unmodeled dynamics, parameter uncertainties and load fluctuations. A GPIO is then designed to estimate the disturbances and high-order time derivatives. By introducing estimations into a PD-type ILC at each iteration, a composite control scheme is obtained, such that the undesirable influence of time-varying disturbances can be effectively attenuated in the repetitive tracking process of manipulators. In this paper, the rigorous stability analysis of the closed-loop system is presented to guarantee that the tracking error exponentially converges to zero as the iteration number tends to infinity. The effectiveness of the proposed control scheme is finally verified by simulation results. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Disturbance rejection

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A Container Cloud Elastic Scaling Method Based on GRU Attention Mechanism

A Container Cloud Elastic Scaling Method Based on GRU Attent...

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Computer Engineering and Intelligent control (ICCEIC) International Conference on

作者： Yue Zhang Yong Sun Chunhe Song Pengpei Gao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798331507992

ISBN: (纸本)9798331508005

In modern container cloud computing environments, achieving efficient elastic scaling is crucial to optimizing resource utilization and improving system performance. This paper proposes a new prediction model based on gated recurrent unit (GRU) and attention mechanism for load prediction and elastic scaling strategy optimization. The model uses the time series processing capability of GRU combined with the optimization characteristics of the attention mechanism to improve the accuracy and real-time performance of load prediction. Experimental results show that compared with traditional methods, the model can more accurately capture the load change trend and achieve more agile and efficient resource scheduling and management, thereby effectively reducing resource waste and improving service quality. This study provides a novel and effective solution for elastic scaling in container cloud environments.

关键词： Cloud computing Attention mechanisms Computational modeling System performance Time series analysis Containers Predictive models Resource management Optimization Load modeling

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A Two-layer Adaptive control Strategy for Photovoltaic Power in Different Scenarios 3

A Two-layer Adaptive Control Strategy for Photovoltaic Power...

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3rd International Conference on Energy Engineering and Power systems, EEPS 2023

作者： Wan, Yanghui Yan, Jiahao Chu, Tianfeng Li, Yaping Yuan, Kun Zhang, Kaifeng Southeast University Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Nanjing China Power Automation Department Nanjing China State Grid Liaoning Electric Power Co. Ltd. Electric Power Research Institute Shenyang China

ISBN: (纸本)9798350313857

Currently, control strategies for distributed photovoltaic (PV) power generation are relatively single and rigid, and cannot flexibly adapt to the diverse demands of power grids in different scenarios. Firstly, this paper analyzes the adaptive relationship between different dispatching demands, the regulation ability of distributed PV, and the characteristics of the local voltage. Secondly, for different scenarios, the coordinated controller determines the reference values of active power and reactive power given to the inverter. Thus, distributed PV power control modes which can adapt to different scenarios have been established. Then, these control modes can be classified into single control modes and compound control modes according to the complexity of scenario demands. On this basis, a specific two-layer adaptive control strategy and process of distributed PV power generation in a low-voltage distribution network are further proposed, which takes into account both external demands of the distribution network and the regulation ability of distributed PV. Finally, a case study is given to verify the rationality and effectiveness of the two-layer adaptive scenarios control strategy. This strategy can effectively improve the comprehensive support ability of distributed PV power generation towards the power grid in multiple scenarios, and improve the stable operation level of the regional power grid. © 2023 IEEE.

关键词： Reactive power

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