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Robust Nonlinear Self-Triggered control Policy for a Novel Fully Actuated UAVs

IFAC-PapersOnLine 2023年第2期56卷 2506-2512页

作者： Zhangzhen Zhu Yongliang Lin Yu Zhang State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province Hangzhou China

This paper proposes a self-triggered control policy for a general kind of nonlinear system, ensuring robust performance under various perturbations and alleviating communication burden simultaneously. A novel fully actuated multirotors applied this method shows great robustness to perturbations and is able of tracking six dimensional decoupled trajectories without continuous background sensor monitoring. Rigorous input-to-state stability analysis is deduced and numerical simulations confirm the validity of the policy.

关键词： UAVs fully actuated event-triggered robustness nonlinear systems

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Protection of Access Pattern 7

Protection of Access Pattern

引用

7th International Conference on Computer Science and Artificial Intelligence, CSAI 2023

作者： Gao, Biao Jia, Shijie Yin, Peng Zhang, Xueying State Key Laboratory of Information Security Institute of Information Engineering Cas School of Cyber Security University of Chinese Academy of Sciences Beijing China Defence Industry Secrecy Examination and Certification Center School of Cyber Security University of Chinese Academy of Sciences Beijing China China Industrial Control Systems Cyber Emergency Response Team Beijing China

ISBN: (纸本)9798400708688

Encryption is insufficient to ensure the system security because the access patterns of user will still reflect the information about the data and serve as an indicator for adversary to infer the sensitive information. We conclude the related work on the access pattern protection to provide a thorough literature review of history independence and oblivious random access machine, which address the issues of static and dynamic access pattern observations respectively. © 2023 Owner/Author.

关键词： Cryptography

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CREPES: Cooperative RElative Pose Estimation System

arXiv

引用

arXiv 2023年

作者： Xun, Zhiren Huang, Jian Li, Zhehan Ying, Zhenjun Wang, Yingjian Xu, Chao Gao, Fei Cao, Yanjun State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China

Mutual localization plays a crucial role in multi-robot cooperation. CREPES, a novel system that focuses on six degrees of freedom (DOF) relative pose estimation for multi-robot systems, is proposed in this paper. CREPES has a compact hardware design using active infrared (IR) LEDs, an IR fish-eye camera, an ultra-wideband (UWB) module and an inertial measurement unit (IMU). By leveraging IR light communication, the system solves data association between visual detection and UWB ranging. Ranging measurements from the UWB and directional information from the camera offer relative 3-DOF position estimation. Combining the mutual relative position with neighbors and the gravity constraints provided by IMUs, we can estimate the 6-DOF relative pose from a single frame of sensor measurements. In addition, we design an estimator based on the error-state Kalman filter (ESKF) to enhance system accuracy and robustness. When multiple neighbors are available, a Pose Graph Optimization (PGO) algorithm is applied to further improve system accuracy. We conduct enormous experiments to demonstrate CREPES’ accuracy between robot pairs and a team of robots, as well as performance under challenging conditions. © 2023, CC BY-NC-ND.

关键词： Multipurpose robots

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Adaptive Wavelet-Positional Encoding for High-Frequency Information Learning in Implicit Neural Representation 39

Adaptive Wavelet-Positional Encoding for High-Frequency Info...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zhao, Hongxu Gao, Zelin Wang, Yue Xiong, Rong Zhang, Yu State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province China

ISBN: (纸本)157735897X

Implicit Neural Representation (INR) has shown great potential in constructing the complex nature signal as a continuous implicit function. However, the representation results are incomplete since different components of the signal correspond to different frequencies and neural network inherently tends to low-frequency convergence. In this paper, we propose the adaptive Wavelet-Positional Encoding (WPE) to precisely represent content under different frequency distributions for coordinate-based implicit representations. The High-Frequency Perception (HFP) method is first proposed to query locations of high-frequency components from input signals, which can be indicated as local centers of WPE. Then, motivated by wavelet series regression, we present to embed these queried low-dimensional coordinate inputs into wavelet-frequency space by WPE to represent fine details of target signals. Experiments demonstrate that the proposed method can be integrated into various INR methods without modifying training frameworks while significantly improving their performance in 1D signal fitting, 2D image regression, and even 3D scene representation. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Network coding

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BEV2PR: BEV-Enhanced Visual Place Recognition with Structural Cues

arXiv

引用

arXiv 2024年

作者： Ge, Fudong Zhang, Yiwei Shen, Shuhan Hu, Weiming Wang, Yue Gao, Jin CASIA China School of Artificial Intelligence University of Chinese Academy of Sciences China School of Information Science and Technology ShanghaiTech University China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University China

In this paper, we propose a new image-based visual place recognition (VPR) framework by exploiting the structural cues in bird’s-eye view (BEV) from a single monocular camera. The motivation arises from two key observations about place recognition methods based on both appearance and structure: 1) For the methods relying on LiDAR sensors, the integration of LiDAR in robotic systems has led to increased expenses, while the alignment of data between different sensors is also a major challenge. 2) Other image-/camera-based methods, involving integrating RGB images and their derived variants (e.g., pseudo depth images, pseudo 3D point clouds), exhibit several limitations, such as the failure to effectively exploit the explicit spatial relationships between different objects. To tackle the above issues, we design a new BEV-enhanced VPR framework, namely BEV2PR, generating a composite descriptor with both visual cues and spatial awareness based on a single camera. The key points lie in: 1) We use BEV features as an explicit source of structural knowledge in constructing global features. 2) The lower layers of the pre-trained backbone from BEV generation are shared for visual and structural streams in VPR, facilitating the learning of fine-grained local features in the visual stream. 3) The complementary visual and structural features can jointly enhance VPR performance. Our BEV2PR framework enables consistent performance improvements over several popular aggregation modules for RGB global features. The experiments on our collected VPR-NuScenes dataset demonstrate an absolute gain of 2.47% on Recall@1 for the strong Conv-AP baseline to achieve the best performance in our setting, and notably, a 18.06% gain on the hard set. Copyright © 2024, The Authors. All rights reserved.

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A Decoupled and Linear Framework for Global Outlier Rejection over Planar Pose Graph

arXiv

引用

arXiv 2022年

作者： Wu, Tianyue Gao, Fei The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China

We propose a robust framework for planar pose graph optimization contaminated by loop closure outliers. Our framework rejects outliers by first decoupling the robust PGO problem wrapped by a Truncated Least Squares kernel into two subproblems. Then, the framework introduces a linear angle representation to rewrite the first subproblem that is originally formulated in rotation matrices. The framework is configured with the Graduated Non-Convexity (GNC) algorithm to solve the two non-convex subproblems in succession without initial guesses. Thanks to the linearity property of the angle representation, our framework requires only a linear solver to optimally solve the optimization problems encountered in GNC. We extensively validate the proposed framework, named DEGNC-LAF (DEcoupled Graduated Non-Convexity with Linear Angle Formulation) in planar PGO benchmarks. It turns out that it runs significantly (sometimes up to over 30 times) faster than the standard and general-purpose GNC while resulting in high-quality estimates. Copyright © 2022, The Authors. All rights reserved.

关键词： Statistics

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CDQKL: Consensus-Based Distributed Quantum Kernel Learning

CDQKL: Consensus-Based Distributed Quantum Kernel Learning

引用

Quantum Communications, Networking, and Computing (QCNC), International Conference on

作者： Wenxuan Ma Mengxiang Liu Ruilong Deng State Key Laboratory of Industrial Control Technology and the College of Control Science and Engineering Zhejiang University Hangzhou China Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

ISBN: (数字)9798350366778

ISBN: (纸本)9798350366785

The field of quantum computing has developed rapidly in recent years due to its promising trend of surpassing traditional machine learning in terms of speed and effectiveness. Quantum kernel learning is one of the paradigms of quantum machine learning, but the training of quantum kernel is time consuming. Therefore, this work makes the first attempt to introduce a consensus-based distributed approach to quantum kernel learning - named CDQKL - that only requires to exchange model parameter information between adjacent nodes while avoiding the need of sharing local training data. Through comparative experimental studies, the advantages of CDQKL in classification accuracy and convergence speed are verified. Considering the popularization of quantum computing cloud service and miniaturization of quantum terminals, the CDQKL adapting to this trend is able to play a vital role in data security, which implies the far-reaching significance of this work. Our code is available at https://***/Leisurivan/CDOKL.

关键词： Training Adaptation models Quantum computing Accuracy Training data Machine learning Market research

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HIDG-based PSO Algorithm: Suspicious Sensor Selection for Power Grid Monitoring System Under Data Integrity Attack 5

HIDG-based PSO Algorithm: Suspicious Sensor Selection for Po...

引用

5th International Conference on Electrical Engineering and control Technologies, CEECT 2023

作者： Li, Pandeng Liang, Zhihong Yang, Yiwei Dong, Liangyu Suo, Yuhan Hao, Yi Electric Power Research Institute Csg Guangdong Provincial Key Laboratory of Power System Network Security Guangdong Guangzhou China China Industrial Control Systems Cyber Emergency Response Team Beijing China Beijing Institute of Technology School of Automation Beijing China

ISBN: (纸本)9798350342253

With the development of communication and sensing technology, it has become possible to monitor the operating status of the power grid system through a series of sensors. However, malicious adversaries may launch data integrity attacks to compromise the measurements of certain sensors, causing the grid monitoring system to fail to grasp the correct system operating status. To solve the NP-hard suspicious sensor selection problem, this paper proposes an efficient attack detection scheduling algorithm, the Particle Swarm Optimization algorithm based on historical information directional guidance (HIDG-based PSO algorithm). The proposed algorithm is utilized with its unique evolutionary mechanism, which reduces the computational power requirements for sensor selection. For the problem of uncertainty in evolutionary algorithms, this paper uses historical information to guide the selection of suspicious sensors at the current moment. The simulation results show that the proposed algorithm can efficiently select suspicious sensors, which will greatly improve the efficiency of attack detection and ensure the security of information fusion of the power grid monitoring system. © 2023 IEEE.

关键词： Scheduling algorithms

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Knowledge Distillation on Driving Intention Generator: Learn Human-like Semantic Reasoning

Knowledge Distillation on Driving Intention Generator: Learn...

引用

IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Hejun Wang Jiajun Dong Yunkai Wang Yanmei Jiao Rong Xiong the State Key Laboratory of Industrial Control Technology and Institute of Cyber-Systems and Control Zhejiang University Hangzhou China the School of Information Science and Engineering Hangzhou Normal University Hangzhou China

Semantic information plays a significant role in autonomous vehicles. However, it has remained open how to economically compute and efficiently incorporate semantic information into other frequently applied processes, such as construction of local navigation map, driving decision making and trajectories planning. To address this issue, we introduce Knowledge Distillation to convey semantic reasoning capability. Following the existing intention-guided framework, a semantically incorporated module associates given navigation instruction with acquired visual perception to synthesize driving intention. Our major contribution is to teach the driving intention generator how to propagate considering semantics implicitly. Specifically, we construct a semantic supervisor identical to the driving intention generator. The supervisor transfers semantic reasoning ability to the generator during training process, with which the generator is expected to perform stably and reliably even in extremely sophisticated surroundings or under frequently inaccurate navigation instruction. Through exhaustive experimental validation, our model demonstrates a superior robustness and adaptability compared to the state-of-the-art. Finally, we explain the intrinsic mechanism of our model with visualization.

关键词：

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Observer-Based SMC for Dynamic Wireless Charging System of Electric Vehicles with Complex Disturbances 18

Observer-Based SMC for Dynamic Wireless Charging System of E...

引用

18th IEEE Conference on industrial Electronics and Applications, ICIEA 2023

作者： Yue, Jiawang Liu, Zhitao Jiang, Zhao Chen, Daidai Su, Hongye Zhejiang University Institute of Cyber-Systems and Control State Key Laboratory of Industrial Control Technology Hangzhou China Northwestern Polytechnical University Ningbo Preh Joyson Automotive Electronics Co. Ltd Ningbo Joyson Advanced Energy Research Institute Co. Ltd Ningbo China Ningbo Joyson Advanced Energy Research Institute Co. Ltd Ningbo China

ISBN: (纸本)9798350312201

This paper focuses on voltage control for a dynamic wireless charging system of electric vehicles based on an extended state observer. Each dynamic wireless charging system will suffer from complex disturbances, leading to the challenge of output voltage control. To address this issue, we propose a disturbance rejection control scheme that utilizes an extended state observer to estimate the unknown disturbances. A dynamic sliding-mode surface is designed to suppress estimation error, and a sliding mode control law based on the estimated information and sliding-mode surface is proposed to accurately track the expected voltage. We prove the stability of the closed-loop system, and simulation results confirm the effectiveness of the proposed disturbance rejection control scheme for dynamic wireless charging systems based on the extended state observer. © 2023 IEEE.

关键词： Disturbance rejection

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