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9th International Conference on Computer and Communications, ICCC 2023

作者： Cai, Xin Xue, Zhenfeng Chen, Zhuo Liu, Yong Huzhou University School of Information Engineering Huzhou313000 China Huzhou Institute of Zhejiang University Intelligent Perception and Control Center Huzhou313098 China Zhejiang University Institute of Cyber-Systems and Control Hangzhou310027 China Cssc Systems Engineering Research Institute Beijing100094 China

ISBN: (纸本)9798350317251

In this paper, we propose a corridor generation algorithm based on voxel extension to obtain a safe path for unmanned surface vehicle (USV). Firstly, a dual-drive model is applied to model the USV, and then we design a path planning framework for the front-end and back-end parts. The front-end structure is responsible for finding a series of asymptotically optimal path points and generating safe corridors connected by a series of convex polygons based on these path points. The back-end part takes the safety corridor as a partial constraint and applies numerical optimization methods to generate a smooth trajectory. Finally, we validate and compare the proposed method with the baseline in a simulation environment. © 2023 IEEE.

关键词： Motion planning

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Dynamic Graph Dismantling with Reinforcement Supervised Learning 42

Dynamic Graph Dismantling with Reinforcement Supervised Lear...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Yumei Tang, Chuancong Zhang, Hai-Tao School of Artificial Intelligence and Automation Huazhong University of Science and Technology The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

There are always some 'key' nodes in a big complex network, which can joint the most connected subgraphs. How to identify these nodes, finding a minimum set of nodes to attack for reducing the size of residual network's Largest Connected Component(LCC) to break up the original network, has become a research hotspot. Therefore, a method for determining the 'key' nodes based on reinforcement learning framework and supervised learning model is proposed. This algorithm can not only utilize the dynamic exploration ability of reinforcement learning to collect a rich training dataset, but also take advantage of the characteristics that supervised learning is adaptive and has strong generalization ability to possess high efficiency and strong robustness. In order to further improve the algorithm's performance, ϵ-greedy mechanism is used to explore more network states. The experiment results show that given the same fraction of removed nodes, our algorithm can make the residual LCC smaller in various networks which is superior to the state-of-the-art algorithms in terms of effectiveness and generalization. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Complex networks

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Towards Consistent Object Detection via LiDAR-Camera Synergy

Towards Consistent Object Detection via LiDAR-Camera Synergy

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Luo, Kai Wu, Hao Yi, Kefu Yang, Kailun Hao, Wei Hu, Rongdong College of Automotive and Mechanical Engineering Changsha University of Science and Technology China School of Traffic and Transportation Engineering Changsha University of Science and Technology China School of Robotics Hunan University China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University China Changsha Intelligent Driving Institute China

ISBN: (纸本)9781665410205

As human-machine interaction continues to evolve, the capacity for environmental perception is becoming increasingly crucial. Integrating the two most common types of sensory data, images, and point clouds, can enhance detection accuracy. Currently, there is no existing model capable of detecting an object's position in both point clouds and images while also determining their corresponding relationship. This information is invaluable for human-machine interactions, offering new possibilities for their enhancement. In light of this, this paper introduces an end-to-end Consistency Object Detection (COD) algorithm framework that requires only a single forward inference to simultaneously obtain an object's position in both point clouds and images and establish their correlation. Furthermore, to assess the accuracy of the object correlation between point clouds and images, this paper proposes a new evaluation metric, Consistency Precision (CP). To verify the effectiveness of the proposed framework, an extensive set of experiments has been conducted on the KITTI and DAIR-V2X datasets. The study also explored how the proposed consistency detection method performs on images when the calibration parameters between images and point clouds are disturbed, compared to existing post-processing methods. The experimental results demonstrate that the proposed method exhibits ex-cellent detection performance and robustness, achieving end-to-end consistency detection. The source code will be made publicly available at https://***/xifen523/COD. © 2024 IEEE.

关键词： Object detection

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A New Automatic User Calibration Algorithm for Three-Dimensional Gaze Estimation

A New Automatic User Calibration Algorithm for Three-Dimensi...

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2022 International Conference on Machine Learning and Knowledge engineering, MLKE 2022

作者： Sun, Hang Chi, Jiannan Ustb School of Automation and Electrical Engineering Beijing China Shunde Graduate School Ustb Foshan China Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Beijing China

ISBN: (纸本)9781665495677

Gaze estimation systems use subject-specific parameters to estimate the user's gaze direction. Advanced remote gaze estimation systems obtain the parameters including the angles between the visual axis and the optical axes of each eye through the automatic calibration algorithms. In these automatic calibration algorithms, the coordinates of the observation surface should be known when calculating the angles between the visual axis and optical axis. However, in head-mounted systems, the coordinates of the observation surface cannot be determined. This paper proposes a new automatic calibration algorithm that does not require the coordinates of the observation surface and subject' active participation in calibration. In order to estimate the angles between the visual and optical axes of each eye, differential evolution algorithms are used to minimize the distance between the visual axes of the left and right eyes while subjects naturally look at the point of gaze (PoG). Simulation results have demonstrated the effectiveness of the algorithm. © 2022 IEEE.

关键词： Eye tracking

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USV Path Planning Based on ACO-SA Algorithm 42

USV Path Planning Based on ACO-SA Algorithm

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42nd Chinese control Conference, CCC 2023

作者： Luo, Chuanshang Tang, Yifeng Huang, Zhihui Xu, Yifan Liu, Bin Zhang, Hai-Tao School of Artificial Intelligence and Automation Huazhong University of Science and Technology The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

This paper solves USV path planning problem constrained by multiple factors via ant-colony optimization algorithm. First, this paper uses the ways of multi-objective optimization to model the USV path planning problem. An improved ant colony algorithm named ACO-SA is put forward afterwards to effectively solve the problem. The algorithm is a combination of ACO algorithm(ant colony algorithm) and SA algorithm(simulated annealing algorithm), which has three improments: change the initial distribution of pheromone to guide the search when the algorithm has just started running;change the heuristic function and state transition probability taking three factors into consideration;change the pheromone update rule and make the ants compete for the right to update pheromone by simulated annealing algorithm, and update the best solution by the same algorithm. Finally, simulation experiment and field experiment are conducted to check the validity of ACO-SA algorithm. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Simulated annealing

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Koopman Operator Learning control of the Piezoelectric Actuator 42

Koopman Operator Learning Control of the Piezoelectric Actua...

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42nd Chinese control Conference, CCC 2023

作者： Huang, Xiang Zhang, Hai-Tao School of Artificial Intelligence and Automation Huazhong University of Science and Technology Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

The piezoelectric actuator is one kind of device that can drive nanoscale motion. However, the nonlinear hysteresis effect induced by its natural material greatly degrades its positioning accuracy. To handle this challenging issue, this work develops a Koopman model predict control (Koopman- MPC) framework for the piezoelectric actuator. Specifically, the Koopman operator theory is adapted for modeling the piezoelectric actuator dynamics. A simple yet powerful linear model spanned in a high-dimensional space is thus constructed to characterize the hysteresis dynamics. Subsequently, upon the established Koopman model, an MPC scheme is put forward for tracking control of piezoelectric actuators. Therein, by sustained optimizing a cost function containing future outputs and control increments, the control input is obtained. Moreover, extensive tracking simulations are carried out on a simulated piezoelectric actuator for verifying the feasibility and effectiveness of the Koopman- Mpc scheme. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Model predictive control

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WDNet: A Water Depth perception Network with Global Information 42

WDNet: A Water Depth Perception Network with Global Informat...

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42nd Chinese control Conference, CCC 2023

作者： Huang, Zhihui Tang, Yifeng Tang, Chuancong Xu, Yifan Luo, Chuanshang Liu, Bin Zhang, Hai-Tao School of Artificial Intelligence and Automation The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

Deep perception of the unmanned surface vehicle's surroundings is an inaccessible part of its fully autonomous navigation mission. The existing methods, whether based on traditional stereo matching or deep learning, do not fully consider the characteristics of water environment, resulting in severe error depths in weak textures (sky, calm lake) and water reflections regions, that increases the risk of running aground or collision. What is worse that there is not a public dataset for depth estimation in the water environment. Therefore, this work proposes a self-supervised model for depth estimation named Water Depth perception Network (WDNet) to address these problems. The decoder of this network has a wider receptive field and can effectively handle the depth error in the weak texture region. Besides, the WDNet is trained with a novel and effective loss function which assist the network to reduce errors in sky and water region, and some indexes are proposed to evaluate the model's performances in sky and water region. Finally, our proposed WDNet achieves a 0.1056 absolute relative error in ranging, the average number of error pixels in the sky area drops from 15803.87 to 580.91, which only accounted for 0.29% of the image, and the error in water region drops from 51.04 to 6.75, all of them are superior to the performance of baseline model. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Errors

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Social Optimization in Noncooperative Games under Central Regulation

arXiv

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arXiv 2025年

作者： Du, Kaixin Meng, Min Li, Xiuxian Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai200092 China Department of Control Science and Engineering College of Electronics and Information Engineering The Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai China

This paper proposes a novel optimization problem building on noncooperative games under central regulation, which can be formulated as a bilevel structure. In the low-level, each player competes to minimize its own cost function that depends not only on the strategies of all players, but also on an intervention decision of the central regulator, while the central regulator located at the high-level attempts to achieve the social optimum, that is, to minimize the sum of cost functions of all players through an adjustable intervention decision. In this setting, under the intervention of the central regulator, the low-level players perform in a noncooperative game and aim to seek the Nash equilibrium, which indeed is related with the regulator’s decision. Meanwhile, the objective of the regulator is to choose a decision such that the social cost, i.e., the sum of cost functions of all players is minimum. This formulated bilevel social optimization problem is proven to be constrained, nonconvex and nonsmooth. To address this intricate problem, an inexact zeroth-order algorithm is developed by virtue of the smoothing techniques, allowing for the Nash equilibrium of the low-level game to be computed in an inexact manner. Levering the properties of smoothing techniques, it is rigorously shown that the devised algorithm achieves a sublinear convergence rate for computing a stationary point of a related optimization problem with a smoothed objective. Moreover, the sublinear convergence rate in the scenario where the exact equilibrium of the low-level game is available is also discussed. Finally, numerical simulations are conducted to demonstrate the efficiency of theoretical findings. Copyright © 2025, The Authors. All rights reserved.

关键词： Cost functions

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Agcm: A Multi-Stage Attack Correlation and Scenario Reconstruction Method Based on Graph Aggregation

SSRN

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SSRN 2024年

作者： Lyu, Hongshuo Liu, Jing Lai, Yingxu Mao, Beifeng Huang, Xianting Faculty of Information Technology Beijing University of Technology Beijing100124 China Engineering Reseach Center Intelligent Perception and Autonomous Control Ministry of Education Beijing100124 China

With an increase in the complexity and scale of networks, cybersecurity faces increasingly severe challenges. For instance, an attacker can combine individual attacks into complex multi-stage attacks to infiltrate targets. Traditional intrusion detection systems (IDS) generate large number of alerts during an attack, including attack clues along with many false positives. Furthermore, due to the complexity and changefulness of attacks, security analysts spend considerable time and effort on discovering attack paths. Existing methods rely on attack knowledgebases or predefined correlation rules but can only identify known attacks. To address these limitations, this paper presents an attack correlation and scenario reconstruction method. We transform the abnornal flows corresponding to the alerts into abnormal states relationship graph (ASR-graph) and automatically correlate attacks through graph aggregation and clustering. We also implemented an attack path search algorithm to mine attack paths and trace the attack process. This method does not rely on prior knowledge;thus, it can well adapt to the changed attack plan, making it effective in correlating unknown attacks and identifying attack paths. Evaluation results show that the proposed method has higher accuracy and effectiveness than existing methods. © 2024, The Authors. All rights reserved.

关键词： Cybersecurity

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Extracting Behavior Events from Epidemic Daily Reports by Combining Deep Learning and Adversarial Training 4

Extracting Behavior Events from Epidemic Daily Reports by Co...

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4th International Conference on Computer, Big Data and Artificial Intelligence, ICCBD+AI 2023

作者： Lin, Shaofu Zhou, Shiwei Xu, Zhe Chen, Jianhui Faculty of Information Technology Beijing University of Technology Beijing China Beijing University of Technology Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China Beijing University of Technology Beijing Key Laboratory of Mri and Brain Informatics Beijing China Ministry of Education Engineering Research Center of Intelligent Perception and Autonomous Control Beijing China Ministry of Education Engineering Research Center of Digital Community Beijing China

ISBN: (纸本)9798350373233

Extracting emergencies from network information has become an important means of public security. However, existing event extraction methods rely on large-scale annotated corpora and are difficult to be effectively applied to extract epidemic behavior events, which is a brand-new task of event extraction. Firstly, an epidemic provenance model is defined to comprehensively model epidemic information in epidemic daily reports. On this basis, we propose an epidemic extraction model of epidemic behavior events, called CBEventMine, that combines deep learning and adversarial training. A relatively simple model structure of BiLSTM+CRF+sigmoid is adopted to achieve fast convergence of the model on small sample data, and an adversarial learning mechanism is added to alleviate the overfitting problem of the model in few-slot learning. The experimental results demonstrate that the proposed model CBEventMine could effectively extract epidemic event than the existing state-of-the-art methods. © 2023 IEEE.

关键词： Extraction

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