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5th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2023

作者： Wang, Gang Lian, Mingchang Ding, Wei Chen, Songhang Chen, Hao Quanzhou Institute of Equipment Manufacturing Haixi Institutes Chinese Academy of Sciences Quanzhou362200 China College of Computer and Cyber Security Fujian Normal University Fujian Fuzhou350001 China Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fujian Fuzhou350108 China Fujian Provincial Key Laboratory of Intelligent Identification and Control of Complex Dynamic System Quanzhou362200 China

ISBN: (纸本)9781643684840

This paper is based on the research background of block relocation in the automated warehouse and proposes a solution utilizing AGV to relocate goods within the warehouse. Building upon the automated warehouse layout and block relocation process, we formulate a mathematical model to minimize the the number of AGV moving goods and the total travel distance of the AGV. To solve the model, we develop an enhanced genetic algorithm, which zones the block relocation process into multiple stages. Each stage integrates conventional heuristic algorithms to enhance the efficiency of the solution process. The improved genetic algorithm can effectively solve the problem, significantly enhancing the automation level of the warehouse. © 2024 The Authors.

关键词： Genetic algorithms

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Transfer function of fluidic system in liquid-circular angular accelerometer

Transfer function of fluidic system in liquid-circular angul...

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IEEE Instrumentation and Measurement technology Conference

作者： Siyuan Cheng Meiling Wang Xiang Li Meifeng Xiao Mengyin Fu Xin Zheng Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Beijing China Nanjing University of Science and Technology Nanjing China The Third Academic of Aerospace and Technology Group of China Beijing China

ISBN: (纸本)9781467392211

In this paper, a new kind of liquid-circular angular accelerometer is studied. Based on electrokinetic phenomenon, this angular accelerometer is designed with a porous transducer and fluid mass. Due to the existence of electrical double layer between transducer and fluid mass, this angular accelerometer is able to convert angular acceleration input to electrical signal. The whole system is composed of fluidic system and molecular electronic system. Theoretical analysis and several experiments are implemented to obtain transfer function model of fluidic system. The flow in transducer satisfies the Darcy Law in the experiment and angular velocity input is proved to have no effect on the output. A prototype is designed to compare the output of theoretical model and experiments. All of the experiments prove that the fluidic system of this liquid-circular angular accelerometer can be seen as a first-order system, especially when the frequency of input is less than 30Hz and its transfer function is derived.

关键词： Transducers Fluids Prototypes Accelerometers Transfer functions Electron tubes Acceleration

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A belief rule-based fault diagnosis method for Multi-UAVs under missing attribute data

A belief rule-based fault diagnosis method for Multi-UAVs un...

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Cyber-Physical Social Intelligence (ICCSI), International Conference on

作者： ErKai Zhao MingRui Hao RuoHan Yang KeYuan Yue DeLin Yu School of Computer Science and Information Engineering Harbin Normal University Harbin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China School of Electronics and Information Northwestern Polytechnical University Xi’an China School of Mathematics and Statistics Northwestern Polytechnical University Xi’an China

To reasonably improve the missing attribute data and effectively integrate sample data and uncertain expert knowledge, this paper proposes a new fault diagnosis method based on a belief rule base (BRB). In the case of missing attribute data, the maximum likelihood estimation (MLE) method is used to complete the missing attribute data, and the fault diagnosis method of the multi-UAVs is constructed by using other complete attribute data as the input information of BRB. Finally, the effectiveness of the proposed method is verified by experimental simulation.

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Real-time terrain estimation based on multi-scale radial basis function for unmanned ground vehicle

Real-time terrain estimation based on multi-scale radial bas...

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International Conference on Information and Automation (ICIA)

作者： Yi Yang Zhili Wang Xinghe Li Mengyin Fu Beijing Institute of Technology Beijing China Nanjing University of Science and Technology Nanjing China School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

ISBN: (纸本)9781509041039

Accurate terrain estimation is essential for unmanned ground vehicle (UGV) to achieve autonomous navigation. However, some existing approaches are difficult to reconstruct the 3D surface in real-time because of serious amount of computation. A method of environmental terrain estimation based on multi-scale radial basis function with a 3D lidar mounted on a moving vehicle was proposed in this paper. By combining kernel template with terrain grid map, the approach is applicable to the non-uniform density distribution of laser point cloud with the increasing detection range and improves the efficiency of calculation. What's more, the estimation of culverts and trees will be more accurate if treat the point cloud in separate layers for suspended obstacles problem. All terrain estimation approaches were verified with good performance in an interactive system, which is set up with Virtual Robot Experimentation Platform (VREP) and actual vehicle.

关键词： Three-dimensional displays Estimation Laser radar Kernel Lasers Surface reconstruction Real-time systems

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Research on guidance method based on angle description

Research on guidance method based on angle description

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Chinese Automation Congress (CAC)

作者： Hui Wang Ruiming Hao Yan Zhen Wugang Wang Yong Wei School of Aerospace Engineeringline Beijing Institute of Technology Beijing China Science and technology on complex system control and intelligent agent cooperation laboratory Beijing China Northwest Industries Group Co.LTD Xian China 672 Test Ground Hua An Industry Group Co. LTD Qiqihaer China

Based on the derivation of optimal proportional navigation, the new expressions with line of sight angle and trajectory angle for proportional navigation, integral proportional navigation and velocity pursuit are proposed. The guidance model with initial heading error is developed when considering a high order dynamics system for the integral proportional navigation and velocity pursuit. Comparative analysis results of miss distance demonstrate the guidance performance of integral proportional navigation and velocity pursuit.

关键词： Navigation Trajectory Missiles Mathematical model Analytical models Acceleration

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

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

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Artificial Intelligence technology (ACAIT), Asian Conference on

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

ISBN: (数字)9798350359145

ISBN: (纸本)9798350359152

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.

关键词： Wavelet transforms Visualization Wavelet domain Noise Lighting Benchmark testing Transformers

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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...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Zirui Wu Zhen Li Dong Zhu Qiuhan Liao Weiran Yao 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: (数字)9798350384185

ISBN: (纸本)9798350384192

The task allocation for multiple robots is a critical component in the coordination of unmanned clusters. The 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 design. This 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 techniques. This model can be trained with varying numbers of robots and tasks without necessitating changes to its structure or parameters. In the experiment of this paper, the model is trained under two different conditions, and the performance is evaluated across six different problem scales. Comparing the proposed model against greedy algorithms and genetic algorithms, the results demonstrate that the proposed model has sianiflcant advantages in overall performance.

关键词： Greedy algorithms Robot kinematics Heuristic algorithms Computational modeling Reinforcement learning Graph neural networks Resource management Unsupervised learning Faces Genetic algorithms

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Cooperative Collision Avoidance Method for Multi-UAV Based on Kalman Filter and Model Predictive control

Cooperative Collision Avoidance Method for Multi-UAV Based o...

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International Conference on Unmanned systems and Artificial Intelligence

作者： Hanqiao Huang Huan Zhou Meiyun Zheng Cheng Xu Xiaofeng Zhang Wei Xiong Unmanned System Research Institute Northwest Polytechnical University Xi'an China Aeronautical Engineering College Air Force Engineering University Xi'an China School of Marine Science and Technology Northwest Polytechnical University Xi'an China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China UAV Researc Center Army Aviation Institute Beijing China

ISBN: (数字)9781728158594

ISBN: (纸本)9781728158600

Collision avoidance is the primary problem to be solved in formation flight of multiple Unmanned aerial vehicles(UAVs). Firstly, a cooperative collision avoidance architecture of multiple UAVs is designed according to the requirement of autonomous collision avoidance of single UAV. Then a new cooperative collision avoidance method of multiple UAVs based on Kalman filter and model predictive control(MPC) is proposed. In this method, extended Kalman filter(EKF) is used to estimate the state of obstacles and target points in uncertain environment space, and to predict the trajectory of obstacles and target points. At the same time, relevant performance index functions and constraints are set up. On the basis of sharing environmental information, model predictive control strategy is used to guide and make cooperative collision avoidance decisions for multiple UAVs. The simulation results show that the proposed method is effective in uncertain environment perception and UAV collision avoidance, and the cooperative mechanism has obvious advantages.

关键词： UAV cooperative decision collision avoidance Kalman filter state estimation MPC Collision avoidance Kalman filters Unmanned Aerial Vehicle State estimation Maximum Allowable Concentration drone honey bees environmental perception Formation flight

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Impact Time and Angle control Guidance Based on Cubic Bézier Curves: Theory and Experiment

SSRN

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SSRN 2024年

作者： Li, Heng Lv, Xiaokang Yu, Jianglong Zhang, Kun Wang, Yanyan Dong, Xiwang Institute of Artificial Intelligence Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Institute of Unmanned System Beihang University Beijing100191 China School of Astronautics Beihang University Beihang University Beijing100191 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing100074 China

A trajectory-shaping guidance strategy with constraints on impact time, impact angle, and maximum lateral acceleration is proposed based on a cubic Bézier curve fitting method. Firstly, an optimal guidance model is formulated, in which the Bézier curves are employed to fit the guidance trajectory, ensuring compliance with the required constraints. The manipulation transforms the optimal guidance problem into an optimal Bézier guidance trajectory design problem and a trajectory tracking problem. Then, by parameterizing the Bézier curves and analyzing the trajectory constraints in detail, the optimal Bézier guidance trajectory design is transformed into optimizing the control parameters of the Bézier curves. Moreover, a multi-layer zeroth-order Adam trajectory optimization algorithm based on general and fine tuning is introduced to determine the control parameters without relying on gradient information. Subsequently, a hyperbolic tangent vector field path tracking guidance algorithm is proposed to follow the designed trajectory and fulfill the guidance missions. Finally, numerical simulations and equivalent physical experiments verify the effectiveness of the proposed guidance strategy. © 2024, The Authors. All rights reserved.

关键词： Trajectories

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Current controller Based on Recurrent Neural Network for Grid-Connected Converter

Current Controller Based on Recurrent Neural Network for Gri...

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第37届中国控制会议

作者： Xuefen Wang Hongbin Wang Qingyi Wang Min Ding Quan Yin School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems State Grid Corporation of China School of Automation Huazhong University of science and technology

Three-phase grid-connected converters are widely used in renewable and electric power system applications. Due to system nonlinearity and time-variant characteristic, there are limitations in standard decoupled d-q vector control mechanism. To mitigate these limitations, a RNN vector controller trained with Levenberg-Marquardt and FATT（Forward accumulation through time） algorithm is designed. The simulation is researched by using MATLAB software, and the results show that training neuralnetwork algorithm is effective and the system using RNN vector control method outperforms the system using conventional PI control method under low sampling rate conditions.

关键词： Grid-connected converter RNN controller LM plus FATT algorithm Simulation

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