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43rd Chinese control Conference, CCC 2024

作者： Liu, Shuqi Wang, Jinhuan Wang, Lin Hebei University of Technology Institute of Mathematics School of Science Tianjin300401 China Shanghai Jiaotong University Key Laboratory of System Control and Information Processing Ministry of Education Department of Automation Shanghai200240 China

ISBN: (纸本)9789887581581

This paper investigates the pricing problem of transportation based on a framework of network congestion game with both player and resource failures. Firstly, the traffic pricing problem is modeled as a network congestion game by redefining the player's cost function in the event of player and resource failures. Secondly, by using the method of semi-tensor product of matrices, the game with player and resource failures is algebraized and verified to be a weighted potential game. The weighted potential function is also obtained. Then, the impact of player and resource failures on Nash equilibria (NEs) is studied, and the condition on keeping the NE of the original game unchanged is discussed. Finally, the theoretical results are verified by numerical examples. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Tensors

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CAEFusion: A New Convolutional Autoencoder-Based Infrared and Visible Light Image Fusion Algorithm

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Computers, Materials & Continua 2024年第8期80卷 2857-2872页

作者： Chun-Ming Wu Mei-Ling Ren Jin Lei Zi-Mu Jiang Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationSchool of Electrical EngineeringNortheast Electric Power UniversityJilin132012China School of Electrical Engineering Northeast Electric Power UniversityJilin132012China School of Electronic Information Engineering Bozhou UniversityBozhou236800China

To address the issues of incomplete information,blurred details,loss of details,and insufficient contrast in infrared and visible image fusion,an image fusion algorithm based on a convolutional autoencoder is *** region attention module is meant to extract the background feature map based on the distinct properties of the background feature map and the detail feature map.A multi-scale convolution attention module is suggested to enhance the communication of feature *** the same time,the feature transformation module is introduced to learn more robust feature representations,aiming to preserve the integrity of image *** study uses three available datasets from TNO,FLIR,and NIR to perform thorough quantitative and qualitative trials with five additional *** methods are assessed based on four indicators:information entropy(EN),standard deviation(SD),spatial frequency(SF),and average gradient(AG).Object detection experiments were done on the M3FD dataset to further verify the algorithm’s performance in comparison with five other *** algorithm’s accuracy was evaluated using the mean average precision at a threshold of 0.5(mAP@0.5)*** experimental findings show that CAEFusion performs well in subjective visual and objective evaluation criteria and has promising potential in downstream object detection tasks.

关键词： Image fusion deep learning auto-encoder(AE) infrared visible light

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Research on Path Planning of Mobile Robot Based on DWA-IMP-A∗ Algorithm 42

Research on Path Planning of Mobile Robot Based on DWA-IMP-A...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Zhi Zhang, Lin Wang, Shoukun Niu, Tianwei Xu, Yongkang Cao, Jin School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Automation Beijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology Beijing100081 China

ISBN: (纸本)9789887581543

Path planning is one of the most critical links in mobile robots. Its timeliness, security and accessibility are crucial to the development and wide application of mobile robots. However, in solving the problem of path planning, the most popular A∗ algorithm has some problems, such as heuristic function cannot be estimated accurately, node redundancy, path is not smooth, and obstacle avoidance cannot be achieved in real time. To solve these problems, A fusion algorithm of improved A∗ combined with reverse path and dynamic window method (DWA-IMP-A∗) was proposed. The algorithm refines the heuristic function by incorporating the reverse path. The node optimization algorithm is used to further reduce the path length. The generated trajectories are smoothed by cubic spline interpolation. At the same time, it is integrated with the improved DWA algorithm to improve the efficiency and safety of robot path planning. The algorithm takes ROS mobile robot as the carrier and is tested under typical road conditions. Compared with A∗ algorithm, the planning time is reduced by 54.6% and the path length is reduced by 6.37%. Experimental results verify the effectiveness and robustness of the algorithm. The research results have certain reference significance for the path planning of various types of mobile robots and the research of driverless vehicles. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Motion planning

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Towards Disturbance Rejection in Feature Pyramid Network

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第4期4卷 946-958页

作者： Hu, Xiaobo Xu, Wei Gan, Yi Su, Jianbo Zhang, Jun Shanghai Jiao Tong University Joint Institute of UM-SJTU Shanghai200240 China Shanghai Jiao Tong University Research Center of Intelligent Robotics Key Laboratory of System Control and Information Processing Ministry of Education Department of Automation Shanghai200240 China

The multiscale problem is one of the challenging topics in the object detection field. Among the current studies toward this problem, feature pyramid network (FPN) has been shown a superior performance. The core principle of FPN is a mapping for the detectable objects into hierarchy features. These features are designed with different size of receptive fields, which brings good scale invariance in the classification and localization subtasks. However, a disturbance of information dilution is generated by the assignment for the detectable objects into different features. This dilution disturbance is associated with the convolution or pooling operation during the hierarchy feature extraction process. Both of the imprecise localization information in the top features and the fuzzy classification information in the bottom ones limit the performance of FPN. Aiming at the disturbance rejection problem of information dilution, this article presents a feature compensation method. A cross compensation between the semantic information and the localization information in hierarchy features is used to enhance the vanilla FPN. Then, the evaluation metrics in an object detection task are examined. Not only the overall performance, but also the respective metrics for multiscale objects validate a considerable improvement of the FPN with a disturbance compensation mechanism. The experimental results demonstrate an effectiveness of the proposed method in this article. © 2020 IEEE.

关键词： Object detection

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Towards Efficient Path Finding and Moving Stability-Focused Trajectory Planning for Mobile Robots

Towards Efficient Path Finding and Moving Stability-Focused ...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Hou, Muyang Lei, Zhenya Hu, Haidong Wang, Zhong Wang, Yong Xie, Le Wang, Hesheng Shanghai Jiao Tong University Department of Automation Shanghai200240 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Beijing Institute of Control Engineering Beijing100190 China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Department of Automation Shanghai200240 China

ISBN: (纸本)9781665481090

Nowadays, mobile robots play an important role in a variety of service scenarios. They need to plan and track trajectories to accomplish tasks such as delivery or guided tours. In such tasks, there are two remaining challenges: on one hand, the time and memory consumption of present path planners are still significant;on the other hand, service robots, which have a higher center of gravity, demand greater moving stability than that of current trajectory planners provide. To address these two challenges. Firstly, we propose a safety boundary first A∗ which fully utilizes environmental obstacle information to create a safety boundary and searches in it to quickly find an initial path. Secondly, we formulate the trajectory optimization problem as a nonlinear optimization problem, where the smoothness, safety, feasibility, and moving stability of the robot are taken into account. Furthermore, to constrain the robot's lateral acceleration, we design a time allocation algorithm based on non-uniform B-spline, enhancing the quality of the resulting trajectory. Simulations and real-world experiments demonstrate that our algorithms significantly improve path search efficiency, enhance moving stability, reduce the difficulty of tracking, and improve the quality of task completion. © 2024 IEEE.

关键词： Trajectories

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SSD object detection algorithm based on knowledge map

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International Journal of Wireless and Mobile Computing 2024年第2期27卷 152-160页

作者： Huang, Li Wang, Xiaofeng Lu, Jianhua Hu, Wei Zhang, Changrong College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan China China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan China Key Laboratory of Metallurgical Equipment and Control Technology of the Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China Precision Manufacturing Research Institute Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Hubei Wuhan China

With the pervasive integration of artificial intelligence into all aspects of human life, talent emerges as a primary resource. Upon analysing the current state of talent training in higher education institutions, issues such as dispersed knowledge points, overlapping content, a singular practice approach and ineffective evaluation have been identified. In response to these challenges, this paper proposes a multidisciplinary and comprehensive practical teaching methodology grounded in the knowledge graph framework. It delves into diverse paths for practical teaching and assessment, including aspects like teaching objectives, problem decomposition, resource integration, implementation methods and performance evaluation. The practical application of the SSD algorithm in researching service robot indoor object detection serves as an illustrative example. Employing the holistic practical teaching approach facilitated by the knowledge graph, this model guides students in acquiring object detection expertise, thereby enhancing their comprehensive development. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Object detection

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Polar-segmented vector optical field and its anomalous focal properties

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Optics Express 2025年第10期33卷 21030-21039页

作者： Gao, Xu-Zhen Song, Xin-Yu Chen, Jing-Rui Wang, Dan Xu, Shi-Tong Niu, Mingsheng Cao, Hongzhong Ma, Rende Pan, Yue School of Physics and Physical Engineering Qufu Normal University Qufu273165 China Shandong Provincial Key Laboratory of Laser Polarization and Information Technology Qufu Normal University Qufu273165 China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education College of Physics and Optoelectronics Taiyuan University of Technology Shanxi Taiyuan030024 China

In recent years, study of spatially structured light has become an attractive and promising area, providing more ways to explore unusual and anomalous effects in optics. Here, we propose a kind of polar-segmented vector optical field (VOF), and demonstrate anomalous focal properties. Due to the appearance of the longitudinal component in tight focusing processes, the transverse energy flow and transverse spin angular momentum (SAM) are achieved, which can be applied in areas such as manipulating particles, as the transverse energy can transport the particles and the SAM can spin the particles in more degrees. Overall, the proposed polar-segmented VOF and the corresponding anomalous focal properties are crucial for advancing theories and technologies in optics, underscoring its importance in both fundamental research and practical applications. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Focusing

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Formation control for Unmanned Surface Vehicles Based on Integrative APF and MPC

Formation Control for Unmanned Surface Vehicles Based on Int...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Li, Weilin Wu, Jing Long, Chengnian Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781665481090

This paper takes the dual water jet propulsion USV as the research object, and studies formation obstacle avoidance optimization problem. An integrative APF algorithm is proposed to merge path planning and trajectory tracking into one optimization problem, where adaptive searching step is adopted to guarantee that the planned trajectory is reachable. In addition, a distance-triggered codesign of integrative APF and MPC is presented to maintain formation during the obstacle avoidance process. Finally, the results in MATLAB simulation demonstrate the validity and efficiency of the algorithm. © 2022 IEEE.

关键词： MATLAB

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Target extraction based on hybrid domain features of array GM-APD lidar 10

Target extraction based on hybrid domain features of array G...

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10th Symposium on Novel Optoelectronic Detection Technology and Applications

作者： Zhang, Xin Li, Sining Sun, Jianfeng Jiang, Peng Jin, Haowei National Key Laboratory of Laser Spatial Information Institute of Opto-Electronic Harbin Institute of Technology Heilongjiang Harbin150001 China Zhengzhou Research Institute of Harbin Institute of Technology Henan Zhengzhou450000 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing100074 China

ISBN: (数字)9781510688155

ISBN: (纸本)9781510688148

This study proposes a target extraction algorithm for array GM-APD lidar based on hybrid domain features, designed to address the challenges of accurately extracting target region based on the image in complex scenes and high noise interference. We extracted the temporal features of the echo signals and transformed the echo signals into the image domain to enhance the information content and further extract image features. By integrating multi-view K-means clustering and AdaBoost classification methods, we introduced a dynamic weight adjustment mechanism and a region adjustment method based on a correlation coefficient to achieve pixel-type discrimination and target region extraction. Experimental results demonstrate that the proposed method exhibits good robustness and adaptability in complex detection environments. Under conditions of different occlusion, different signal-to-noise ratios, and different target reflectivity, the proposed algorithm significantly outperforms traditional region-growing segmentation methods in terms of accuracy of target region extraction. © 2025 SPIE.

关键词： K-means clustering

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Stabilization of a class of fuzzy stochastic jump systems with partial information on jump and sojourn parameters

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Science China(Technological Sciences) 2021年第2期64卷 353-363页

作者： CAI Bo WENG Rui ZHANG RuiXian LIANG Ye ZHANG LiXian School of Astronautics Harbin Institute of TechnologyHarbin 150001China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai 200240China

This paper addresses the problem of the design of controller for fuzzy semi-Markov jump systems with hidden modes against the incomplete information on probability density functions of sojourn time. Two ubiquitous circumstances in practice are taken into account, which are often ignored in other related work:(1) the phenomenon that system modes cannot be accessed entirely is considered proactively;(2) finitely accessible information on probability density functions is studied in this paper. By virtue of hidden semi-Markov chain, the underlying systems are modeled as hidden semi-Markov jump systems, which are more general than semi-Markov jump systems. Sufficient conditions on the existence of desired accessible-mode-dependent fuzzy controller are derived such that the fuzzy hidden semi-Markov jump systems is mean square stable. Based on the emission probability matrix, the presented control policy overcomes the possible mode-mismatch between the system mode and the accessible ***, an example is provided to demonstrate the effectiveness of the proposed control method.

关键词： hidden modes probability density function stochastic switching systems time-varying controller Takagi-Sugeno(T-S)fuzzy system

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