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<title cf:type="text"><![CDATA[Editorial department of the Journal of National University of Defense Technology -->专栏： 自主无人系统技术前沿进展]]></title>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Review on motion planning methods for unmanned aerial vehicle cooperative maneuvering flight in cluttered environment]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202204001]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[The basic principle, representative methods, and state-of-the-art research of the sub-module related research within the general framework of cooperative maneuvering flight planning from single UAV (unmanned aerial vehicle) maneuvering flight to multi-UAV cooperative planning were introduced. It mainly included real-time navigation map construction, discrete-space path planning, continuous-space trajectory planning, hybrid planning based on discrete-space and continuous-space, and multi-courses/trajectories cooperative planning. The next research directions were proposed based on the major technologies of the planning framework.]]></description>
<pubDate>2022/7/20 0:00:00</pubDate>
<category><![CDATA[专栏： 自主无人系统技术前沿进展]]></category>
<author><![CDATA[NIU Yifeng, LIU Tianqing, LI Jie, JIA Shengde]]></author>
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<atom:name>NIU Yifeng, LIU Tianqing, LI Jie, JIA Shengde</atom:name>
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<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202204001]]></guid><cfi:id>13</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Occlusion and confusion targets recognition method for UAV under small sample conditions]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202204002]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[Aiming at the problem of occlusion and confusion targets recognition for UAV (unmanned air vehicle) under small sample conditions, a target recognition model integrating self-attention mechanism and few-shot learning was proposed. On the basis of using the idea of meta learning to obtain the ability of few-shot learning, the self-attention mechanism to learn the context dependence between the internal parts of the target was introduced into the model, so as to enhance the target representation ability and solve the problem of insufficient effective features in the case of occlusion and confusion. In order to verify the effect of the model, the occlusion and confusion target datasets were constructed by further processing the reference datasets and UAV aerial photography data, and different occlusion degrees and background confusion rates were set. Through the verification on different datasets and compared with the deep learning model, the proposed model is proved to possess higher learning efficiency and recognition accuracy.]]></description>
<pubDate>2022/7/20 0:00:00</pubDate>
<category><![CDATA[专栏： 自主无人系统技术前沿进展]]></category>
<author><![CDATA[WU Lizhen, LI Hongnan, NIU Yifeng]]></author>
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<atom:name>WU Lizhen, LI Hongnan, NIU Yifeng</atom:name>
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<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202204002]]></guid><cfi:id>12</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Unmanned aerial vehicle swarm cooperative search based on moth pheromone courtship mechanism]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202204003]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[In order to improve the efficiency of the UAV (unmanned aerial vehicle) swarm in cooperative search for moving targets, a UAV swarm cooperative search method was proposed on the basis of the moth pheromone courtship mechanism. According to the courtship behavior of moth in choosing flight direction by pheromone, a wind direction model in pheromone map and a moth pheromone courtship model were established. Considering the constraint of collision avoidance between UAV swarm, a map from moth pheromone courtship mechanism to UAV swarm distributed cooperative search was proposed, and the specific implementation process was given. Simulation results show the effectiveness and stability of the proposed method in solving the cooperative search problem of single moving target, and the outdoor flight experimental results verified the feasibility of the proposed method in practice.]]></description>
<pubDate>2022/7/20 0:00:00</pubDate>
<category><![CDATA[专栏： 自主无人系统技术前沿进展]]></category>
<author><![CDATA[LIU Yunhao, DENG Yimin, DUAN Haibin, WEI Chen]]></author>
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<atom:name>LIU Yunhao, DENG Yimin, DUAN Haibin, WEI Chen</atom:name>
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<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202204003]]></guid><cfi:id>11</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Model predictive based disturbance rejection and obstacle avoidance guidance for multi-rotor unmanned aerial vehicle]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202204004]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[The autonomous obstacle avoidance of UAV (unmanned aerial vehicle) is the basis of completing complex tasks, and the obstacle avoidance performance directly affects the efficiency of UAV performing tasks. Aiming at the obstacle avoidance problem of UAV with external disturbance, a design method of anti-disturbance and obstacle avoidance guidance law based on model prediction was proposed. The disturbance observer was designed to estimate the external disturbance in the system dynamics, and the auxiliary guidance law was designed based on Lyapunov function method to establish the stability constraints. Combining the first two with MPC (model predictive control), the relationship between UAV and obstacles was considered in the MPC optimization solution, and the horizontal linear velocity and yaw angular velocity commands were solved according to the designed guidance law to realize the obstacle avoidance of UAV. The numerical simulation and physical flight verification of the proposed obstacle avoidance guidance law show the effectiveness of the proposed method.]]></description>
<pubDate>2022/7/20 0:00:00</pubDate>
<category><![CDATA[专栏： 自主无人系统技术前沿进展]]></category>
<author><![CDATA[LAN Qingxiang, CHEN Mou, YONG Kenan]]></author>
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<atom:name>LAN Qingxiang, CHEN Mou, YONG Kenan</atom:name>
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<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202204004]]></guid><cfi:id>10</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Solution to continuous time Markov chain model for unmanned aerial vehicle swarm operation]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202204005]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[In order to solve the problem of low computing speed in the process of state transition in the analytical modeling of UAV (unmanned aerial vehicle) swarm operation, a fourth-order Runge-Kutta method based on the row compressed storage was proposed. The UAV swarm operation process was divided into three stages according to the UAV swarm operation style, and continuous time Markov chain model was established for the state transition process of UAV swarm operation in stages. In the meantime, taking the reliability of UAV swarm to complete combat mission as the solving index, the fourth-order Runge-Kutta method was used to solve the Markov model, and the method based on row compressed storage was used to optimize the solving rate owing to the sparsity feature of the rate transfer matrix. Simulation results show that the established continuous time Markov chain model has better effectiveness and feasibility than other models. At the same time, compared with other algorithms, the proposed algorithm has higher computing speed and better reliability requirements to meet the accuracy of results, which further shows the superiority of it.]]></description>
<pubDate>2022/7/20 0:00:00</pubDate>
<category><![CDATA[专栏： 自主无人系统技术前沿进展]]></category>
<author><![CDATA[HUANG Shucai, XIE Jiahao, WEI Daozhi, ZHANG Zhaoyu]]></author>
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<atom:name>HUANG Shucai, XIE Jiahao, WEI Daozhi, ZHANG Zhaoyu</atom:name>
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<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202204005]]></guid><cfi:id>9</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[DWA path planning algorithm based on multi-objective particle swarm optimization in complex environment]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202204006]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[When the robot is running in a complex environment with densely distributed obstacles, the DWA (dynamic window approach) algorithm is prone to obstacle avoidance failure or unreasonable planning. In this regard, an improved DWA planning algorithm based on MOPSO(multi-objective particle swarm optimization) was proposed. Based on the establishment of multi obstacle environment coverage model, a method was put forward for judging obstacle-dense areas in complex environments. And the original DWA algorithm was improved by optimizing the sub-evaluation functions. On these basis of the improved MOPSO algorithm, the adaptive change of DWA weight coefficients were transformed into a multi-objective optimization problem. According to the requirements of path planning, the safety distance and speed can be set as the optimization goals, moreover, the corresponding multi-objective optimization model was established. The results of a series of simulations show that this method enables the robot to effectively pass through the dense area of obstacles while taking account of the safety and speed of operation, and has better path planning effect.]]></description>
<pubDate>2022/7/20 0:00:00</pubDate>
<category><![CDATA[专栏： 自主无人系统技术前沿进展]]></category>
<author><![CDATA[LI Xinying, SHAN Liang, CHANG Lu, QU Yi, ZHANG Yong]]></author>
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<atom:name>LI Xinying, SHAN Liang, CHANG Lu, QU Yi, ZHANG Yong</atom:name>
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<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202204006]]></guid><cfi:id>8</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Optimal control method for swarm systems formation tracking problem with linear quadratic regulator performance index]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202204007]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[For the formation tracking problem for swarm systems, an optimal control method with linear quadratic regulator performance index was put forward.Establish the mathematical description of the formation tracking problem and design a formation tracking control protocol. Necessary and sufficient conditions for swarm systems with formation tracking were obtained and the stability of the system was analysed by using the second method of Lyapunov.Topology conditions of the control protocol which can minimize linear quadratic regulator performance index were obtained and the formation tracking algorithm was designed.A numerical simulation was provided to illustrate the effectiveness of the control method.]]></description>
<pubDate>2022/7/20 0:00:00</pubDate>
<category><![CDATA[专栏： 自主无人系统技术前沿进展]]></category>
<author><![CDATA[WANG Lin, ZHANG Qingjie, CHEN Hongwei]]></author>
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<atom:name>WANG Lin, ZHANG Qingjie, CHEN Hongwei</atom:name>
</atom:author>
<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202204007]]></guid><cfi:id>7</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Analysis of dynamic inductance gradient of electromagnetic rail launcher]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202203019]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[A mathematical calculation model of armature inductance gradient under the conditions of uniform and non-uniform magnetic field distribution between guide rails was deduced. The velocity frequency was introduced to simulate the velocity skin effect of armature emission process, and the time-harmonic simulation analysis was carried out on the 2D and the 3D electromagnetic field model. The inductance coefficient and the inductance gradient obtained from the simulation were used to calculate the dynamic inductance and the dynamic armature force in the simulation system. Electrical simulation and experiment results show that both the current and the velocity error are less than 2%, which proves the correctness and accuracy of dynamic inductance gradient analysis and parameter extraction method.]]></description>
<pubDate>2022/6/2 10:28:11</pubDate>
<category><![CDATA[专栏： 自主无人系统技术前沿进展]]></category>
<author><![CDATA[ZHAI Xiaofei, LI Xinhang, LIU Hua, PENG Zhiran]]></author>
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<atom:name>ZHAI Xiaofei, LI Xinhang, LIU Hua, PENG Zhiran</atom:name>
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<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202203019]]></guid><cfi:id>6</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Target detection in SAR images based on joint generative adversarial network and detection network]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202203020]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[Aiming at the problem of difficult and limited sample acquisition in SAR(synthetic aperture radar) image target detection, a learning model of joint GAN (generative adversarial network) and detection network was proposed. The original training set was used to pretrain the specially designed faster regional convolutional neural network. The deep convolutional GAN based on attention mechanism was employed to generate extensive synthetic samples, which were input into the detection network for prediction. The corresponding annotation information of the new samples was determined by the prediction information and probability equivalent class label allocation strategy, and the annotated new samples were used to expand the original dataset with a certain proportion. The detection network was retrained with the expanded dataset. Simulation results show that the proposed framework can improve the detection efficiency and performance of the network effectively.]]></description>
<pubDate>2022/6/2 10:28:11</pubDate>
<category><![CDATA[专栏： 自主无人系统技术前沿进展]]></category>
<author><![CDATA[HAN Zishuo, WANG Chunping, FU Qiang, ZHAO Bin]]></author>
<atom:author xmlns:atom="http://www.w3.org/2005/Atom">
<atom:name>HAN Zishuo, WANG Chunping, FU Qiang, ZHAO Bin</atom:name>
</atom:author>
<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202203020]]></guid><cfi:id>5</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Estimation of submarine underwater corrosion electric field based on equivalent circuit and point current source]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202203021]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[In order to quickly evaluate the underwater corrosion electric field in the damaged state of the submarine coating, the corrosion current equivalent circuit of submarine coating local damage was established based on the principle of electrochemical corrosion and the characteristics of submarine structure, and the corrosion current intensity of submarine coating local damage was calculated. The corrosion electric field of submarine was modeled based on the point current source. The damaged part of submarine coating and exposed propeller were equivalent to point current source. The calculation formula of electric field of point current source in layered medium was used to estimate the corrosion stable electric field in the damaged state of the submarine coating. Compared with the simulation results of the commercial finite element software COMSOL for the corrosion electric field of a certain submarine, the results show that the submarine surface corrosion current and the electric field distribution curves of different paths obtained by this estimation method are basically consistent with the simulation results of COMSOL, the relative error of current calculation value does not exceed 6.5%,and the relative error of peak to peak value of each electric field component does not exceed 18%.]]></description>
<pubDate>2022/6/2 10:28:11</pubDate>
<category><![CDATA[专栏： 自主无人系统技术前沿进展]]></category>
<author><![CDATA[ZHAO Yulong, LIU Chunyang, ZHOU Dan]]></author>
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<atom:name>ZHAO Yulong, LIU Chunyang, ZHOU Dan</atom:name>
</atom:author>
<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202203021]]></guid><cfi:id>4</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Decision tree algorithm for packet classification]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202203022]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[Packet classification is the fundamental function of network, and researchers have proposed many packet classification solutions in the past two decades. Among them, the decision tree algorithm for packet classification has received extensive attention and in-depth research due to its high throughput, suitable for multiple fields and pipelining. The recent research on the decision tree algorithm for packet classification was introduced, the geometric meaning, common techniques and test benchmarks of the decision tree algorithm were described, and the decision tree algorithm from the two dimensions of node cutting technology and rule set grouping technology were systematically analyzed. The typical algorithms of the two types of common technologies for building decision tree were introduced respectively, the design ideas and characteristics of various algorithms were compared, and their applicable scenarios were given. The conclusion and discuss the future work of decision tree algorithms were stated out.]]></description>
<pubDate>2022/6/2 10:28:11</pubDate>
<category><![CDATA[专栏： 自主无人系统技术前沿进展]]></category>
<author><![CDATA[LYU Gaofeng, TAN Jing, QIAO Guanjie, YAN Jinli]]></author>
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<atom:name>LYU Gaofeng, TAN Jing, QIAO Guanjie, YAN Jinli</atom:name>
</atom:author>
<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202203022]]></guid><cfi:id>3</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Image segmentation algorithm combining hierarchical clustering algorithm and graph-based segmentation algorithm]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202203023]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[Based on the GBS(graph-based segmentation) algorithm and the hierarchical clustering algorithm, a method to solve the under-segmentation of GBS algorithm was constructed. Meanwhile, the way of multi-threaded parallel processing of data was used to effectively improve the processing speed of the traditional hierarchical clustering algorithm. In the RGB color space, the GBS algorithm was used to obtain the initial segmentation result of each pixel in the image. The pixel value in each type of region was extracted and the hierarchical clustering was carried out to obtain the category label of pixel value in each type of region. According to the category label obtained by hierarchical clustering and the preset category range, the initial segmentation result of each pixel was modified. A new segmentation graph was generated according to the region merging criterion. Experimental results show that compare with the K-means-SLIC algorithm and the GBS algorithm, this method solves the phenomenon of under-segmentation, and produces a semantic segmentation graph with high segmentation accuracy.]]></description>
<pubDate>2022/6/2 10:28:11</pubDate>
<category><![CDATA[专栏： 自主无人系统技术前沿进展]]></category>
<author><![CDATA[GUO Xingang, WANG Jia, CHENG Chao]]></author>
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<atom:name>GUO Xingang, WANG Jia, CHENG Chao</atom:name>
</atom:author>
<guid><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202203023]]></guid><cfi:id>2</cfi:id><cfi:read>true</cfi:read></item>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Hesitant fuzzy rough set decision-making method for determining spare parts variety of new small-scale equipment]]></title>
<link><![CDATA[http://journal.nudt.edu.cn/gfkjdxxben/article/abstract/202203024]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[Aiming at the problem that the prominent features of hesitancy and fuzziness of decision information and it′s difficult to use the traditional method to determine the varieties of spare parts for new equipment of small scale, a method of determining the varieties of spare parts based on hesitating fuzzy rough sets was proposed. The risk preference coefficient was used to extend the incomplete hesitancy information, which laid a foundation for establishing the hesitancy information system for different risk preference. Considering the influence of the score function and the numerical continuation boundary, an improved inclusion degree formula was given and proved on the basis of the definition of inclusion degree. The reduction condition and rule acquisition method of spare parts varieties decision attribute based on the improved inclusion calculation were given, which realized the depth mining and effective utilization of hesitancy and decision information. The results show that this method can deal with hesitancy and decision information effectively, and obtain a simplified and practical decision rule set of spare parts varieties, and the feasibility of the method was verified.]]></description>
<pubDate>2022/6/2 0:00:00</pubDate>
<category><![CDATA[专栏： 自主无人系统技术前沿进展]]></category>
<author><![CDATA[YANG Chao, HOU Xingming, CHEN Xiaowei, QIN Haifeng, ZHANG Linlin]]></author>
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<atom:name>YANG Chao, HOU Xingming, CHEN Xiaowei, QIN Haifeng, ZHANG Linlin</atom:name>
</atom:author>
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