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Real-Time Implementation of Quadrotor UAV Control System Based on a Deep Reinforcement Learning Approach

Computers, Materials & Continua 2024年第12期81卷 4757-4786页

作者： Taha Yacine Trad Kheireddine Choutri Mohand Lagha Souham Meshoul Fouad Khenfri Raouf Fareh Hadil Shaiba Aeronautical Sciences Laboratory Aeronautical and Spatial Studies InstituteBlida 1 UniversityBlida0900Algeria Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Energy and Embedded Systems for Transportation Research Department ESTACA-LABMontigny-Le-Bretonneux78066France Department of Electrical Engineering University of SharjahSharjah27272United Arab Emirates Department of Computer Science College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

The popularity of quadrotor Unmanned Aerial Vehicles(UAVs)stems from their simple propulsion systems and structural ***,their complex and nonlinear dynamic behavior presents a significant challenge for control,necessitating sophisticated algorithms to ensure stability and accuracy in *** strategies have been explored by researchers and control engineers,with learning-based methods like reinforcement learning,deep learning,and neural networks showing promise in enhancing the robustness and adaptability of quadrotor control *** paper investigates a Reinforcement Learning(RL)approach for both high and low-level quadrotor control systems,focusing on attitude stabilization and position tracking tasks.A novel reward function and actor-critic network structures are designed to stimulate high-order observable states,improving the agent’s understanding of the quadrotor’s dynamics and environmental *** address the challenge of RL hyper-parameter tuning,a new framework is introduced that combines Simulated Annealing(SA)with a reinforcement learning algorithm,specifically Simulated Annealing-Twin Delayed Deep Deterministic Policy Gradient(SA-TD3).This approach is evaluated for path-following and stabilization tasks through comparative assessments with two commonly used control methods:Backstepping and Sliding Mode Control(SMC).While the implementation of the well-trained agents exhibited unexpected behavior during real-world testing,a reduced neural network used for altitude control was successfully implemented on a Parrot Mambo mini *** results showcase the potential of the proposed SA-TD3 framework for real-world applications,demonstrating improved stability and precision across various test scenarios and highlighting its feasibility for practical deployment.

关键词： Deep reinforcement learning hyper-parameters optimization path following quadrotor twin delayed deep deterministic policy gradient and simulated annealing

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Anionic covalent organic framework electrolyte with tailored ion channels for high-areal-capacity solid-state lithium metal battery

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science China Chemistry 2025年第4期68卷 1533-1540页

作者： Xu Zhuang Yangdan Hui Yangyang Feng Jiajie Chen Junlan Chen Yaobing Wang College of Chemistry Institute of Molecular Engineering PlusFuzhou UniversityFuzhou 350116China CAS Key Laboratory of Design and Assembly of Functional Nanostructures and Fujian Provincial Key Laboratory of NanomaterialsState Key Laboratory of Structural ChemistryFujian Institute of Research on the Structure of MatterChinese Academy of SciencesFuzhou 350002China Fujian Science and Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou 350108China University of Chinese Academy of Sciences Beijing 100049China Fujian College University of Chinese Academy of SciencesFuzhou 350002China

Covalent organic frameworks(COFs)are an emerging class for solid-state electrolytes due to their ordered and customizable ion transport *** high ionic conductivity(σ_(Li+))and Li^(+) transference number(t_(Li+))are achieved;the high-arealcapacity solid-state lithium metal battery(LMB)still encountered challenges;which is mainly determined by homogeneous Li^(+) flux through channels and ***;we design a COF coupling anionic skeletons with branched ion-conductive chains(COF-S)as tailored fast ion-transport channels to achieve high-areal-capacity solid-state *** the dispersed COF-S-based electrolyte is further obtained by incorporating ethoxylated trimethylolpropane triacrylate(ETPTA)and Li FSI(ETPTA-COF-S)via in situ light *** this way;the abundant SO_(3)-groups promote Li+adsorption and facilitate axial transport via 1D channels;thus enabling highσLi+of 1.29 m S cm^(-1)and tLi+of *** branched chains can tailor ion channels to suppress largesize anions transport;disperse and uniform Li+flux;thus leading to high average Coulombic efficiency(CE)up to 98.43%for 100 cycles(~800 h)at 0.5 m A cm^(-2)under the high areal capacity of 2 mAh cm^(-2).When paired with 2 m Ah cm^(-2)LiFePO_(4)(LFP)cathode and thin Li anode of 20μm;Li||ETPTA-COF-S||LFP exhibits superior cyclic stability for 80 cycles.

关键词： covalent organic framework ion channel sulfonic acid group gel electrolyte lithium metal battery high areal capacity

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Compact Dual-Band Dual-Circularly Polarized Stacked Microstrip Antenna 15

Compact Dual-Band Dual-Circularly Polarized Stacked Microstr...

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15th International Conference on Microwave and Millimeter Wave technology, ICMMT 2023

作者： Wang, Ting Wang, Jun Zhao, Lei China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Xidian University Science and Technology on Antenna and Microwave Laboratory Xi'an710071 China

ISBN: (纸本)9798350338874

A compact dual-band dual-circularly polarized antenna is proposed in this paper. The designed antenna adopts two radiation patches which are placed on two layers substrate respectively to achieve circularly polarized waves with different rotation directions. The simulated results show that the antenna operates at low frequency (12.5GHz) with left-handed circular polarization (LHCP) and high frequency (14.25GHz) with right-handed circular polarization (RHCP). The simulated gain of the dual-circularly polarized antenna is 3.4dBic at 12.5GHz and 3.9dBic at 14.25GHz, respectively. The structure of this antenna is simple and has a small size of 0.37λ0∗0.37λ0∗0.038λ0 (where λ0 is free-space wavelength at 12.5GHz), which have potential applications for Ku-band satellite communication. © 2023 IEEE.

关键词： Circular polarization

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Simulation analysis of compression overlap time rate influence on flow pulsation in double reciprocating ultraclean bellows pump 9

Simulation analysis of compression overlap time rate influen...

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9th International Conference on Fluid Power and Mechatronics, FPM 2023

作者： Luo, Yanyuan Gu, Xiaowei Shen, Huimin Hu, Liang University of Shanghai for Science and Technology shanghai China School of Mechanical Engineering State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou China

ISBN: (纸本)9798350304947

The traditional double reciprocating ultraclean bellows pump has a significant flow pulsation due to the minimum output flow, when one side of the bellows discharge ends and the other side begins to discharge. To reduce this pulsation, both sides of the bellows pump can be put under compression at the same time. This configuration allows both sides to be in the discharge process concurrently, effectively reducing the flow pulsation. This article analyzes influence of compression overlap time rate on flow pulsation in double reciprocating ultraclean bellows pump based on the COMSOL Multiphysics simulation platform. A three-dimensional dynamic mesh numerical model of bellows pump was established. Then the fluid solid interactions process in the bellows of the pump is simulated and analyzed to determine how different overlap time rates affect the flow pulsation at the pump's outlet. © 2023 IEEE.

关键词： Pumps

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A Wide Beam Structurally Embedded High-Temperature Resistant Traveling Wave End-Fire Ceramic-Monoblock Antenna 11

A Wide Beam Structurally Embedded High-Temperature Resistant...

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11th IEEE Asia-Pacific Conference on Antennas and Propagation, APCAP 2023 - Proceedings

作者： Tao, Jiayi Yang, Zhitao Deng, Hongwei Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering Nanjing210016 China Science and Technology on Space Physics Laboratory Beijing China

ISBN: (纸本)9798350326277

A high-temperature resistant ceramic-monoblock dielectric rod antenna operating at Ku-band is designed with thermal protection shield and thermal insulation material. Part of the ceramic-monoblock structure is plated with copper as a rectangle waveguide, and the other part includes the radiation and transition sections, which are embedded in the center of the radome as the traveling wave end-fire dielectric rod antenna. The end-fire characteristics of the antenna can reduce the impact on the surrounding environment and achieve -8 dBi gains within the range of |theta| © 2023 IEEE.

关键词： ceramic-monoblock antenna high-temperature resistant antenna traveling wave end-fire antenna wide beam

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Average Sum Rate Optimization in RIS-Assisted NOMA Satellite Network: A Deep Reinforcement Learning Approach

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IEEE Wireless Communications Letters 2025年第6期14卷 1772-1776页

作者： Fu, Shu Wei, Wei Feng, Xue Yin, Liuguo Chongqing University Department of Microelectronics and Communication Engineering Chongqing400044 China Civil Aviation Administration of China Key Laboratory of Flight Techniques and Flight Safety Beijing China Tsinghua University Beijing National Research Center for Information Science and Technology Beijing100084 China

Satellite-ground communication network will be an important network architecture in the coming six generation (6G). In this letter, we formulate a reconfigurable intelligent surface (RIS) assisted non-orthogonal multiple access (NOMA) satellite network to improve the poor wireless channel gain caused by long-distance transmission between the satellite and the ground. To maximize the system average sum rate, we joint optimize the phase-shift matrix of RIS, user pairing and power allocation. Specifically, we propose a novel algorithm named PPO-DQN which merging the proximal policy optimization (PPO) and deep Q-network (DQN) algorithm to effectively solve the optimization problem with both continuous variables and discrete variables. Finally, the effectiveness of the proposed algorithm is verified through various simulations. © 2012 IEEE.

关键词： Deep reinforcement learning

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Network Security Situation Prediction Based on TCAN-BiGRU Optimized by SSA and IQPSO

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Computer systems science & engineering 2023年第10期47卷 993-1021页

作者： Junfeng Sun Chenghai Li Yafei Song Peng Ni Jian Wang College of Air and Missile Defence Air Force Engineering UniversityXi’an710051China Science and Technology on Complex Aviation Systems Simulation Laboratory Beijing100076China

The accuracy of historical situation values is required for traditional network security situation prediction(NSSP).There are discrepancies in the correlation and weighting of the various network security *** solve these problems,a combined prediction model based on the temporal convolution attention network(TCAN)and bi-directional gate recurrent unit(BiGRU)network is proposed,which is optimized by singular spectrum analysis(SSA)and improved quantum particle swarmoptimization algorithm(IQPSO).This model first decomposes and reconstructs network security situation data into a series of subsequences by SSA to remove the noise from the ***,a prediction model of TCAN-BiGRU is established respectively for each *** uses the TCN to extract features from the network security situation data and the improved channel attention mechanism(CAM)to extract important feature information from *** learns the before-after status of situation data to extract more feature information from sequences for ***,IQPSO is proposed to optimize the hyperparameters of ***,the prediction results of the subsequence are superimposed to obtain the final predicted *** the one hand,IQPSO compares with other optimization algorithms in the experiment,whose performance can find the optimum value of the benchmark function many times,showing that IQPSO performs *** the other hand,the established prediction model compares with the traditional prediction methods through the simulation experiment,whose coefficient of determination is up to 0.999 on both sets,indicating that the combined prediction model established has higher prediction accuracy.

关键词： Network security situation prediction SSA IQPSO TCAN-BiGRU

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Demo Abstract: Range-SLAM: UWB based Realtime Indoor Location and Mapping 23

Demo Abstract: Range-SLAM: UWB based Realtime Indoor Locatio...

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23rd ACM/IEEE International Conference on information Processing in Sensor Networks, IPSN 2024

作者： Liu, Yi Jian, Zhuozhu Tan, Junbo Liang, Lunfei Liu, Houde Chen, Xinlei Shandong University School of Information Science and Engineering China Harbin Institute of Technology School of Mechatronics Engineering China Tsinghua University Shenzhen International Graduate School China Pengcheng Laboratory China RISC-V International Open Source Laboratory China

ISBN: (纸本)9798350362015

Simultaneous localization and mapping (SLAM) systems frequently employ LiDAR and cameras as essential sensing components. However, these sensors are proved to be unreliable in environments with poor visibility or reflective surfaces. And UWB (Ultra Wide Band) sensor with a longer wavelength shows better potential to achieve perception tasks. However, since UWB sensors can only obtain distance information from the anchors, it is difficult to densely construct the geometric structure of the environment. In this paper, We propose Range-SLAM, a method based on received signal strength indicator (RSSI) recognition and binary filtering to complete the mapping task and enhance positioning based on the map, and only require UWB as external perception sensor. Real-world experiments are conducted and prove the effectiveness, real-time performance and robustness of the Range-SLAM algorithm. © 2024 IEEE.

关键词： Mapping

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NEAT-Net: An Unsupervised Cross-View Prior Inpainting Network for CBCT Metal Artifact Reduction 46

NEAT-Net: An Unsupervised Cross-View Prior Inpainting Networ...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Yang, Yang Tong, Zhan Zhong, Xinyun Shi, Yijie Xi, Yan Yu, Wenxue Wu, Zhan Chen, Yang First-Imaging Tech Shanghai China Southeast University Laboratory of Image Science and Technology The School of Computer Science and Engineering Nanjing China Southeast University Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing The Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Nanjing China

ISBN: (纸本)9798350371499

Intraoperative Cone-Beam Computed Tomography (CBCT) facilitates intraoperative navigation for Minimally Invasive Spine Surgery (MISS). However, high-attenuation metal implants used in MISS often cause metal artifacts in the reconstructed CBCT images. Current algorithms do not consider the cross-view information in the projection-domain for metal artifact reduction (MAR). Inaccurate projection-domain inpainting results in CBCT MAR lead to tissue blurring and secondary artifacts, significantly compromising the accuracy of CBCT-guided MISS and increasing surgical risks. To address the above challenge, in this paper, we propose a novel unsupervised cross-view prior inpainting network for CBCT Metal Artifact Reduction named NEAT-Net. Firstly, a cross-view prior multi-scale inpainting module is constructed to learn the inter-view complementary information. Secondly, a hybrid feature attention module is proposed to adaptively fuse cross-view features. In addition, an unsupervised training approach is proposed to directly learn from metal-affected data. Extensive experiments are conducted to verify the effectiveness of our algorithm on a real clinical dataset. © 2024 IEEE.

关键词： Computerized tomography

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Pavement Cracks Coupled With Shadows:A New Shadow-Crack Dataset and A Shadow-Removal-Oriented Crack Detection Approach

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IEEE/CAA Journal of Automatica Sinica 2023年第7期10卷 1593-1607页

作者： Lili Fan Shen Li Ying Li Bai Li Dongpu Cao Fei-Yue Wang School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Civil Engineering Tsinghua UniversityBeijing 100084China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body and the College of Mechanical and Vehicle Engineering Hunan UniversityChangsha 410082China School of Vehicle and Mobility Tsinghua UniversityBeijing 100084China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Automatic pavement crack detection is a critical task for maintaining the pavement stability and driving *** task is challenging because the shadows on the pavement may have similar intensity with the crack,which interfere with the crack detection *** to the present,there still lacks efficient algorithm models and training datasets to deal with the interference brought by the *** fill in the gap,we made several contributions as ***,we proposed a new pavement shadow and crack dataset,which contains a variety of shadow and pavement pixel size *** also covers all common cracks(linear cracks and network cracks),placing higher demands on crack detection ***,we designed a two-step shadow-removal-oriented crack detection approach:SROCD,which improves the performance of the algorithm by first removing the shadow and then detecting *** addition to shadows,the method can cope with other noise ***,we explored the mechanism of how shadows affect crack *** on this mechanism,we propose a data augmentation method based on the difference in brightness values,which can adapt to brightness changes caused by seasonal and weather ***,we introduced a residual feature augmentation algorithm to detect small cracks that can predict sudden disasters,and the algorithm improves the performance of the model *** compare our method with the state-of-the-art methods on existing pavement crack datasets and the shadow-crack dataset,and the experimental results demonstrate the superiority of our method.

关键词： Automatic pavement crack detection data augmentation compensation deep learning residual feature augmentation shadow removal shadow-crack dataset

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