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检索条件"机构=Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory"

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A Multi-Robot Task Allocation Method Based on Graph Attention Network and Unsupervised Learning

A Multi-Robot Task Allocation Method Based on Graph Attentio...

引用

2024 IEEE International Conference on Unmanned systems, ICUS 2024

作者： Wu, Zirui Li, Zhen Zhu, Dong Liao, Qiuhan Yao, Weiran School of Astronautics Harbin Institute of Technology Harbin China Beijing Electro-Mechanical Engineering Institute Beijing China Chengdu CHG Robots & Intelligent Equipment Institute Co. Ltd. Chengdu China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (纸本)9798350384185

The task allocation for multiple robots is a critical component in the coordination of unmanned *** existing heuristic algorithms are hard to achieve satisfactory results in large-scale problems, and reinforcement learning-based methods face challenges in ensuring the rationality of reward *** paper introduces a model based on multi-head attention and graph neural networks to address the schedule-dependent multi-robot task allocation problem, trained using unsupervised learning *** model can be trained with varying numbers of robots and tasks without necessitating changes to its structure or *** the experiment of this paper, the model is trained under two different conditions, and the performance is evaluated across six different problem *** the proposed model against greedy algorithms and genetic algorithms, the results demonstrate that the proposed model has significant advantages in overall performance. © 2024 IEEE.

关键词： Adversarial machine learning

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Monocular Visual-Inertial Odometry Based on Point and Line Features

Monocular Visual-Inertial Odometry Based on Point and Line F...

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International Conference on Computer and Communications (ICCC)

作者： Gongyan Chen Hai Zhang Wenxing Fu Yiqun Qiao School of Automation Science and Electrical Engineering Beihang University Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

In order to solve the problem that the point feature tracking is not robust enough to reduce the accuracy of the system in a low-texture environment, this paper proposes a visual inertial odometry system based on point-line features (PL-VINS). Firstly, the system improves the extraction and matching algorithm of line features to increase the speed and accuracy of the algorithm; then the line features are added to the front-end tracking and back-end optimization. Finally, the EuRoc public data set is used as the experimental object to prove the effectiveness of the algorithm.

关键词： Visualization Conferences Feature extraction Cameras Real-time systems Optimization Optical flow

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Prescribed-Time Clusters Flocking for Multi-agent systems of UAVs and USVs 6

Prescribed-Time Clusters Flocking for Multi-Agent Systems of...

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6th International Conference on Electronic Engineering and Informatics, EEI 2024

作者： Shang, Hanjun Wang, Zhenhuan Tian, Yingxin Hou, Qimin Kuang, Jiyuan Gao, Yabin School of Astronautics Harbin Institute of Technology Harbin150001 China Elite Engineers School Harbin Institute of Technology Harbin150001 China The National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing100074 China School of Software Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)9798350353594

This paper deals with the problem of clusters flocking for a heterogeneous multi-agent system of Unmanned Aerial Vehicles (UAVs) and Unmanned Surface Vessels (USVs). The dynamics models of the UAVs and USVs are established separately. Due to the different state dimensions and dynamics models of the UAVs and USVs, the two types of agents are formulated with two clusters. Then, the functions of formation errors of the two clusters are constructed. For the two clusters, a new type of prescribed-time formation control laws is designed respectively. Moreover, compared with the conventional formation control that can only ensure that the multi-agent system completes ideal formations without strict time constraints theoretically, the present prescribed-time control laws can enable the multi-agent system to complete ideal formation strictly at a prescribed time independent of initial formation errors. Finally, the effectiveness of the prescribed-time formation control is verified by simulations. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Topology Optimization Design of LEO Satellite Network

Topology Optimization Design of LEO Satellite Network

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第三十八届中国控制会议

作者： Jian Tai Junting Lv XiANDe Wu Ting Song Qiang Zhang Yanbing Xiang Jun Sun College of Aerospace and Civil Engineering Harbin Engineering University Shanghai Key Laboratory of Space Intelligent Control Technology Beijing Institute of Spacecraft System Engineering Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory

This paper establishes a satellite network topology optimization model based on satellite orbital dynamics, establishes constraints from two aspects of satellite geometric visibility and satellite elevation constraints in the concept of inter-satellite links, and finally solves the above optimization problems by using simulated annealing algorithm, and presents a time-varying satellite network topology optimization method. In the actual simulation, we give a satellite network with multiple satellites and optimize it. The optimal solution of the network configuration is obtained, and a shortest inter-satellite transmission path from signal start star to signal termination star based on time-varying is solved. For this inter-satellite link, the connectivity of inter-satellite link and the fault tolerance of satellite network are analyzed, which proves the feasibility and validity of the optimization method.

关键词： LEO satellite network topology optimization inter-satellite link simulated annealing algorithm

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A Hierarchical Graph Search Method for Path Planning of Unmanned Ground Vehicle for Freight Transportation

A Hierarchical Graph Search Method for Path Planning of Unma...

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2024 IEEE International Conference on Unmanned systems, ICUS 2024

作者： Hu, Jianing Li, Zhen Guo, Sen Yao, Weiran School of Astronautics Harbin Institute of Technology Harbin China Beijing Electro-Mechanical Engineering Institute Beijing China CRRC Nanjing Puzhen Co. Ltd. Nanjing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (纸本)9798350384185

For the problem of collision volume change when forklift unmanned vehicles work in complex storage environments, a multi-level graph search path planning method is proposed. The first level is the path planning of the Unmanned Ground Vehicle (UGV) body, which uses the grid map and the A* algorithm to plan the path of the UGV transferring in the scene;the second level is the joint path planning of the UGV and the object being carried, to avoid overcomplicating this issue, the unmanned vehicle will be limited to pushing the cargo only forwards. The third level is the path planning when the unmanned vehicle carries multiple objects, which decomposes the whole scene into multiple sub-scenes, plans the paths of the unmanned vehicle in the sub-scenes separately, and searches for the optimal combination of sub-scenes. Higher level searches will invoke lower level algorithms and provide a virtual scene and target as input. The experimental results show that this multilevel path planning method is optimal and complete in solving the forklift unmanned vehicle for handling a single object, and can give a feasible solution for handling multiple objects. © 2024 IEEE.

关键词： Ground vehicles

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An Improved Robust Adaptive Kalman Filtering Algorithm

An Improved Robust Adaptive Kalman Filtering Algorithm

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第三十八届中国控制会议

作者： Liuyang Jiang Wenxing Fu Hai Zhang Zheng Li Longyun Chi School of Automation Science and Electrical Engineering Beihang University Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory National Airspace Management Center

Robust adaptive Kalman filter(RAKF) is a method that can not only compensate for the model errors but also resist the measurement outliers. The method reduces the influence of the measurement outliers on the filtering system by reducing the weight of the abnormal observation. After the processing of robust estimation, all the errors are attributed to the inaccuracy of the model. Since the robust estimation is not theoretically quantitative that it can only reduce the observation error to a certain extent, the remaining observation errors are compensated as the model errors, resulting in new estimation errors. To address this problem, a method for detecting the model error is proposed as a trigger condition for RAKF to compensate for the model error,and this constitutes an improved robust adaptive Kalman filter(IRAKF) algorithm. The new algorithm performs the model errors compensation stricter than the original method. The efficacy of the improved algorithm is demonstrated via a traffic running testing with GPS/INS tight integration navigation system. Simulation results indicate that the improved algorithm can effectively reduce the inaccurate adaptive procedure and obtain relatively accurate and stable filtering results.

关键词： Adaptive Kalman Filter Robust Estimation Improved Model Errors Tight Integrated Navigation

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A Generic Anti-Windup Design Under Linear Active Disturbance Rejection control Scheme

A Generic Anti-Windup Design Under Linear Active Disturbance...

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Electrical, Automation and Computer Engineering (ICEACE), International Conference on

作者： Li Hui Xu Cheng Ji Hua Yin Zhide Hu Wanhai Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China The 3rd Research Academy of CASIC Beijing China

A generic anti-windup compensation strategy under Linear Active Disturbance Rejection control scheme is proposed. The difference, between the controller output and the actuator output, after multiplied by a tunable parameter, together with controller output, is fed back to the extended state observer to compensate controller windup. While windup problem arises in control system, the controller output is expectedly produced, and the disadvantageous influence of nonlinearity on closed-loop dynamics is distinctly alleviated. The approach is employed to a near space vehicle with fin-deflection saturation. The numerical simulations show that the proposed approach has the better effectiveness in active disturbance rejection control designed situation than some previous anti-windup compensation strategy.

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WATNet: A Wavelet-Aware Lightweight Hybrid Model for Fast Low-Light Enhancement 7

WATNet: A Wavelet-Aware Lightweight Hybrid Model for Fast Lo...

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7th Asian Conference on Artificial Intelligence technology, ACAIT 2023

作者： Wang, Qiangqiang Huang, Peiliang Li, Lei Han, Longfei Anhui University AHU-IAI Ai Joint Laboratory Hefei China Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei China Northwestern Polytechnical University School of Automation Xi'an China Science And Technology On Complex System Control And Intelligent Agent Cooperation Laboratory Beijing China Beijing Technology And Business University Beijing China University of Science And Technology of China School of Information Science And Technology Hefei China

ISBN: (纸本)9798350359145

Low-light enhancement task is an essential component of computer low-level visual tasks, which involves processing images captured under dim lighting conditions to make them appear as if they were taken under normal illumination. Currently, deep neural networks have become the mainstream approach for image processing. However, recent works have devoted considerable efforts to designing high-performance models, which often come with high computational complexity and inference time, making real-time processing unfeasible. We observed that some convolutional methods are due to the need for deep layers which results in a large number of parameters. Moreover, enhancing details and removing noise in low-light images remains an open challenge. In order to solve the above problems, we propose a lightweight baseline that combines CNN and sparse grid attention transformer blocks to enable the model to capture a global receptive field at an early stage. Specifically, we propose a High-Frequency Wavelet-aware Block(HFWB) that focuses on processing high-frequency information in the wavelet domain to refine details and suppress noise. With a processing time of only 10.6ms, the performance of our model outperforms that of the current state-of-the-art lightweight models on benchmark low-light datasets. Compared to state-of-the-art models in the LOL dataset, our model achieves a reduction in inference time of over 90% and requires only about 1% of the FLOPS. © 2023 IEEE.

关键词： Deep neural networks

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Failure Mode and Effects Analysis of UAV Power system Based on Generalized Dempster-Shafer Structures

Failure Mode and Effects Analysis of UAV Power System Based ...

引用

IEEE International Conference on Unmanned systems (ICUS)

作者： Zhuo Zhang Mingrui Hao School of Electronics and Information Northwestern Polytechnical University Xian China Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728137933

The unmanned aerial vehicle(UAV) power system consists of components that provide flight power for the UAV, which mainly includes three parts: motor, electronic speed controller(ESC), and battery. Since the UAV always operates in the open air, which requires high stability of the power system, the failure mode and effects analysis(FMEA) is particularly significant and it has been widely used to examine potential failures in systems or components. However, the traditional FMEA method has many unreasonable points. In order to better deal with the uncertainty and improve the stability of the UAV power system, we propose a FMEA method which is based on the generalized Dempster-Shafer structures, the failure modes are comprehensively analyzed and the risks are ranked by combining the characteristic information of risk factors with the generalized evidence theory. The new method can not only deal with the uncertainty of risk assessment, but also further improve the reliability of effects analysis. In addition, the FMEA experiment of the UAV power system is carried out in this paper. The experimental results show that the method is effective for practical applications.

关键词： Failure mode and effects analysis Generalized dempster-Shafer stucture Fuzzy set theory Unmanned aerial vehicle power system Failure Mode and Effect Analysis Unmanned Aerial Vehicle drone honey bees Fuzzy Set Theory FAILURE MODES power systems Power system stability

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Edge-guided image estimation for array Gm-APD Lidar in smoky environment using multi-scale depth images 6

Edge-guided image estimation for array Gm-APD Lidar in smoky...

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6th Optics Young Scientist Summit, OYSS 2023

作者： Zhang, Yinbo Li, Sining Sun, Jianfeng Jiang, Peng Zhang, Hailong Liu, Zhihui Zhu, Yuebing National Key Laboratory of Science and Technology on Tunable Laser Institute of Opto-Electronic Harbin Institute of Technology Heilongjiang Harbin150001 China Zhengzhou Research Institute of Harbin Institute of Technology Henan Zhengzhou450000 China Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing100074 China Sichuan Jiuzhou Electrical Group Company Limited Sichuan Mianyang621000 China

ISBN: (纸本)9781510672642

Limited statistical frame number and strong backscatter interference from smoke result in a photon-starved regime, severely limiting the depth imaging capability of array Gm-APD lidar in smoky environment. Here, we propose a depth image estimation algorithm that can significantly improve the integrity of targets in dense smoke environments when signal photons are starved. At the signal level, the algorithm improves the accuracy of extracting signal photons by constructing multi-scale superpixels. At the image level, using edge information of depth images at different scales to guide and fill the original scale depth image achieves efficient noise reduction and improves target integrity. It has been successfully demonstrated under different attenuation lengths and statistical frame numbers. Compared with other state-of-the-art methods, the proposed algorithm has maximum target recovery and structural similarity, especially for the attenuation length (AL) is 3.6 and statistical frame number is 1500 (imaging time is 75ms). This study is of great significance for the fast depth imaging of dynamic targets by array Gm-APD lidar in dense smoke environments. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Optical radar

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