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IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR)

作者： Xiang Bai Junyi Wang Xiaofeng Xiong Evangelos Boukas Applied Mathematics and Computer Science Technical University of Denmark Copenhagen Denmark Automation and Control Group Electrical and Photonics Engineering Technical University of Denmark Copenhagen Denmark SDU Biorobotics Mærsk Mc-Kinney Møller Institute University of Southern Denmark Odense Denmark

ISBN: (数字)9798331516857

ISBN: (纸本)9798331516864

This paper aims at a deep reinforcement learning (DRL) controller for fast (< 1.5s) manipulation of a flexible tool (i.e., whip) to hit a target in 3D space. The controller consists of a DRL algorithm for optimizing joint motions, and a proportional-derivative (PD) mechanism for tracking the optimized motions. Their objective is to minimize the distance between the whip-end-tip and the target. The proposed controller was validated in a 7-DOF robot arm by comparing four DRL algorithms in the physical simulator MuJoCo. It shows that the proximal policy optimization (PPO) outperforms others by obtaining the maximum average reward. Notably, PPO can still effectively interact with the environment under sparse or even unrewarding conditions, making it a robust choice for complex and dynamic tasks. Our work provides preliminary knowledge of DRL applications to fast robotic arm control in flexible object manipulation.

关键词： Three-dimensional displays Target tracking Heuristic algorithms Programming Aerospace electronics Deep reinforcement learning Manipulators Optimization Autonomous robots

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Publishing Social Graphs with Differential Privacy Guarantees Based on wPINQ

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Chinese Journal of Electronics 2019年第2期28卷 273-279页

作者： LI Xiaoye YANG Jing SUN Zhenlong ZHANG Jianpei College of Computer Science and Technology Harbin Engineering University College of Computer and Control Enginewaeering Qiqihar University

To publish social graphs with differential privacy guarantees for reproducing valuable results of scientific researches, we study a workflow for graph synthesis and propose an improved approach based on weighted Privacy integrated query(wPINQ). The workflow starts with a seed graph to fit the noisy degree sequence, which essentially is the 1K-graph. In view of the inaccurate assortativity coefficient, we truncate the workflow to replace the seed graph with an optimal one by doing target 1K-rewiring while preserving the 1K-distribution. Subsequently, Markov chain Monte Carlo employs the new seed graph as the initial state, and proceeds step by step guided by the information of Triangles by intersect to increase the number of triangles in the synthetic graphs. The experimental results show that the proposed algorithm achieves better performance for the published social graphs.

关键词： Differential privacy Social networks weighted Privacy integrated query(wPINQ) dK-graph model

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Reconfigurable Intelligent Surface Enhanced Wireless Localization: Phase Optimization for Malicious Interference Mitigation

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IEEE Transactions on Communications 2025年

作者： Zhang, Yi Xie, Yajing Wang, Lijia Liwang, Minghui Wang, Xianbin Xiamen University Ministry of Education of China Department of Information and Communication Engineering Key Laboratory of Multimedia Trusted Perception and Efficient Computing Xiamen China Tongji University Shanghai Research Institute for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai China Western University Department of Electrical and Computer Engineering ON Canada

Recently, unmanned aerial vehicles (UAVs) and reconfigurable intelligent surfaces (RISs) have merged as important enabling technologies for localization coverage extension and localization accuracy improvement under signal blockage and malicious interference conditions. However, most existing works assume known locations of jammers, which is generally impractical in real-world networks. To overcome this challenge, we propose a novel RIS-enhanced wireless localization framework against malicious interference with the support of either narrowband or orthogonal frequency division multiplexing (OFDM) pilot signals. A two-stage anti-jamming localization approach is developed to first estimate the unknown channel and signal information of the jammer and then localize the user’s position by eliminating the jamming signal. More importantly, we utilize the full potential of RIS to improve localization accuracy by optimizing the phase shift profile during the iterative process. Extensive simulation results demonstrate the commendable performance of our proposed framework, which can not only mitigate the jamming effect but also achieve better localization accuracy, offering a good reference for future heterogeneous and complex wireless networks. © 1972-2012 IEEE.

关键词： Frequency division multiplexing

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Blockage-Resilient Integrated Sensing and Communication in mmWave Networks: Multi-View Collaboration and Efficient Task Allocation

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IEEE Transactions on Mobile Computing 2025年

作者： Cui, Yue Ding, Haichuan Ma, Ying Li, Xuanheng Zhang, Haixia Fang, Yuguang Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China Beijing Institute of Technology School of Information and Electronics Beijing100081 China Dalian University of Technology School of Information and Communication Engineering Dalian116023 China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Shandong University Shandong Provincial Key Laboratory of Wireless Communication Technologies School of Control Science and Engineering Jinan250061 China City University of Hong Kong Department of Computer Science Hong Kong Hong Kong

Integrated sensing and communication (ISAC) has emerged as a promising technology for future millimeter wave (mmWave) networks. However, the susceptibility of mmWave signals to blockages poses considerable challenges for ISAC as it can result in unreliable links and disrupted sensing. As a result, this paper investigates the blockage-resilient ISAC design that leverages the robustness offered by multi-base station (BS) collaboration. Given the dynamic blockages and the fluctuation in the targets' radar cross section (RCS), the blockage-resilient multiBS collaborative ISAC design is cast as a chance constrained integer programming (CCIP) by jointly considering the diverse deadlines of different sensing tasks and the spatial/temporal user-target pairing for dual-functional radar and communication (DFRC) waveform scheduling. To facilitate efficient solution finding, we develop a group concatenating assisted reinforcement learning (GCRL) algorithm, where we linearize the chance constraints via variable grouping and concatenation, enabling the RL agent to understand the problem structure with bipartite graphs so as to develop an efficient branching policy. Extensive experiments demonstrate the resilience of the obtained ISAC scheme to dynamic blockages. © 2025 IEEE. All rights reserved.

关键词： Integer programming

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A Reducing Iteration Orthogonal Matching Pursuit Algorithm for Compressive Sensing

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Tsinghua science and Technology 2016年第1期21卷 71-79页

作者： Rui Wang Jinglei Zhang Suli Ren Qingjuan Li School of Computer and Communication Engineering University of Science and Technology Beijing School of Computer and Control Engineering University of Chinese Academy of Sciences

In recent years, Compressed Sensing（CS） has been a hot research topic. It has a wide range of applications, such as image processing and speech signal processing owing to its characteristic of removing redundant information by reducing the sampling rate. The disadvantage of CS is that the number of iterations in a greedy algorithm such as Orthogonal Matching Pursuit（OMP） is fixed, thus limiting reconstruction ***, in this study, we present a novel Reducing Iteration Orthogonal Matching Pursuit（RIOMP） algorithm that calculates the correlation of the residual value and measurement matrix to reduce the number of *** conditions for successful signal reconstruction are derived on the basis of detailed mathematical *** compared with the OMP algorithm, the RIOMP algorithm has a smaller reconstruction error. Moreover, the proposed algorithm can accurately reconstruct signals in a shorter running time.

关键词： compressed sensing signal processing wireless sensor networks

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SHIELD: Assessing Security-by-Design in Federated Data Spaces Using Attack Graphs 25

SHIELD: Assessing Security-by-Design in Federated Data Space...

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Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing

作者： Alessandro Palma Nikolaos Papadakis Georgios Bouloukakis Joaquin Garcia-Alfaro Mattia Sospetti Kostas Magoutis Department of Computer Control and Management Engineering 00185 Sapienza University of Rome Rome Italy Samovar Télécom SudParis Institut Polytechnique de Paris 91120 Télécom SudParis Institut Polytechnique de Paris Palaiseau France France GrottiniLab S.r.L. Porto Recanati Macerata Italy Computer Science Department University of Crete University of Crete Crete Greece Greece Institute of Computer Science (ICS) - Hellas (FORTH) Hellas (FORTH) Crete Greece Greece

ISBN: (纸本)9798400706295

Federated data spaces allow organizations to share and control their own data across various domains, but their exposure to cyber attacks has increased due to a surge in newly discovered vulnerabilities. Existing solutions to secure them focus on messaging protocol protection (e.g., using cryptographic means), but this is not sufficient. Attackers may exploit additional vulnerabilities to cause significant issues (e.g., disrupting the availability of services). To this end, we propose SHIELD, a security-by-design approach for federated data spaces, which leverages attack graphs and trust computation to mitigate the risks of cyber attacks. Mitigation is accomplished by proactively assessing the data spaces' weaknesses and implementing security messaging measures to prevent detrimental attacks. A prototype implementation of SHIELD using publish/subscribe as a messaging mechanism is experimentally evaluated over a real architecture in a V2X (Vehicle-to-Everything) scenario.

关键词： federated data spaces

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Motion Direction Awareness: A Biomimetic Dynamic Capture Mechanism for Video Prediction

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IEEE Transactions on Multimedia 2025年

作者： Gan, Lianqiang Lai, Junyu Zhu, Junhong Liu, Huashuo Gao, Lianli University of Electronic Science and Technology of China School of Aeronautics and Astronautics Chengdu611731 China University of Electronic Science and Technology of China School of Aeronautics and Astronautics China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province Chengdu611731 China University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China

Video prediction is an important yet challenging task that generates future frames based on previous observations. Despite recent progress, existing methods still suffer from motion blur, due to weak motion perception capabilities leading to uncertainty in motion direction. To address this, we propose a Motion Direction Awareness (MDA) mechanism inspired by the direction-selective mechanism in animal visual systems. Specifically, MDA can decompose complex motions into horizontal and vertical components, allowing dimension reduction and independent processing, thereby effectively enhancing motion perception and reducing uncertainty in predicted motion directions. Based on MDA, we design a multi-scale feature fusion network named MDANet for video prediction, which incorporates different scales of spatially encoded features in conjunction with MDA mechanism to extract the temporal evolution information of global and local spatial features. Extensive experiments on representative datasets demonstrate that MDANet can alleviate motion blurring, improving prediction accuracy and temporal consistency over state-of-the-art models. Furthermore, we validate the generalizability and effectiveness of our MDA mechanism by integrating it into other advanced models. The code is available at supplementary. © 1999-2012 IEEE.

关键词： Deep learning

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Self–triggered Scheme Design for Takagi–Sugeno Fuzzy Model based on Mismatch Premise Variable With Time–varying Delay

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IEEE Transactions on Automation science and engineering 2025年 22卷 15536-15548页

作者： Aslam, Muhammad Shamrooz Bilal, Hazrat Vasilakos, Athanasios V. China University of Mining and Technology Artificial Intelligence Research Institute Xuzhou 2211106 China College of Mechatronics and Control Engineering College of Computer Science and Software Engineering Shenzhen University Shenzhen 518060 China College of Computer Science and Information Technology IAU Department of Networks and Communications P.O. Box 1982 Dammam 31441 Saudi Arabia Center for AI Research (CAIR) University of Agder(UiA) Grimstad Norway

Over the last 20 years, numerous experts in the manufacturing companies have become interested in controlling flexible joint robots. The control design process using a networked framework has played a significant role in the industrial sector. This research addresses the self–triggered control problem for Takagi–Sugeno (T–S) fuzzy systems based on time delay is established in this research. A new self–triggered mechanism determines when the plant state is transmitted. Instead of continuously tracking predefined triggering conditions, the self–triggered system determines the next triggering instant based on the most recently triggered state information. The self–triggered mechanism relying on T–S fuzzy controller is then created using the triggered state, allowing for flexible configuration of its fuzzy rules and membership operations (MOs) that are not dependent on the controlled fuzzy system. Furthermore, it precisely demonstrates the interaction between the triggered condition and the plant state under the constraint of mismatched premise variables. To ensure system stability and performance, delay–dependent requirements are derived using a novel Lyapunov–Krasovskii functional based on fuzzy concepts to develop the fuzzy control design. The presence of the required controller is then shown under LMI–based conditions. Lastly, a simulation of a flexible robotic arm example is provided along with an evaluation of other triggered methods. © 2004-2012 IEEE.

关键词： Mismatch premise variable Robotic Arm Self–triggered control T–S Fuzzy Model

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Switching Multiplicative Watermark Design Against Covert Attacks

arXiv

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arXiv 2025年

作者： Gallo, Alexander J. Anand, Sribalaji C. Teixeira, Andre M.H. Ferrari, Riccardo M.G. Department of Electronics Information and Bioengineering Politecnico di Milano Milano Italy School of Electrical Engineering and Computer Science and Digital Futures KTH Royal Institute of Technology Sweden Department of Information Technology Uppsala University PO Box 337 UppsalaSE-75105 Sweden Delft Center for Systems and Control Mechanical Engineering TU Delft Delft Netherlands

Active techniques have been introduced to give better detectability performance for cyber-attack diagnosis in cyber-physical systems (CPS). In this paper, switching multiplicative watermarking is considered, whereby we propose an optimal design strategy to define switching filter parameters. Optimality is evaluated exploiting the so-called output-to-output gain of the closed loop system, including some supposed attack dynamics. A worst-case scenario of a matched covert attack is assumed, presuming that an attacker with full knowledge of the closed-loop system injects a stealthy attack of bounded energy. Our algorithm, given watermark filter parameters at some time instant, provides optimal next-step parameters. Analysis of the algorithm is given, demonstrating its features, and demonstrating that through initialization of certain parameters outside of the algorithm, the parameters of the multiplicative watermarking can be randomized. Simulation shows how, by adopting our method for parameter design, the attacker’s impact on performance diminishes. © 2025, CC BY-NC-ND.

关键词： Networked control systems

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Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation

arXiv

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arXiv 2025年

作者： Liu, Jian Sun, Wei Yang, Hui Deng, Pengchao Liu, Chongpei Sebe, Nicu Rahmani, Hossein Mian, Ajmal National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering School of Robotics State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China Department of Information Engineering and Computer Science University of Trento Trento38123 Italy School of Computing and Communications Lancaster University LA1 4YW United Kingdom Department of Computer Science The University of Western Australia WA6009 Australia

Nine-degrees-of-freedom (9-DoF) object pose and size estimation is crucial for enabling augmented reality and robotic manipulation. Category-level methods have received extensive research attention due to their potential for generalization to intra-class unknown objects. However, these methods require manual collection and labeling of large-scale real-world training data. To address this problem, we introduce a diffusion-based paradigm for domain-generalized category-level 9-DoF object pose estimation. Our motivation is to leverage the latent generalization ability of the diffusion model to address the domain generalization challenge in object pose estimation. This entails training the model exclusively on rendered synthetic data to achieve generalization to real-world scenes. We propose an effective diffusion model to redefine 9-DoF object pose estimation from a generative perspective. Our model does not require any 3D shape priors during training or inference. By employing the Denoising Diffusion Implicit Model, we demonstrate that the reverse diffusion process can be executed in as few as 3 steps, achieving near real-time performance. Finally, we design a robotic grasping system comprising both hardware and software components. Through comprehensive experiments on two benchmark datasets and the real-world robotic system, we show that our method achieves state-of-the-art domain generalization performance. Our code will be made public at https://***/CNJianLiu/Diff9D. Copyright © 2025, The Authors. All rights reserved.

关键词： Augmented reality

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