2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)最新文献_第5页

Using CNN With Handcrafted Features for Prostate Cancer Classification 使用CNN与手工制作的特征进行前列腺癌分类

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230297

Yimo Liu, Di Bu, Guokai Zhang, Ye Luo, Jianwei Lu, Weigang Wang, Binghui Zhao

引用次数: 2

Filters navigation and positioning based on mining vehicle motion model 基于矿用车辆运动模型的滤波导航定位

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230004

Yuheng Chen, Hongyun Wu, Zhou Liu, Yongfeng Liu, Jingwei Li, Bolin Yin

{"title":"Filters navigation and positioning based on mining vehicle motion model","authors":"Yuheng Chen, Hongyun Wu, Zhou Liu, Yongfeng Liu, Jingwei Li, Bolin Yin","doi":"10.1109/CACRE50138.2020.9230004","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230004","url":null,"abstract":"The navigational positioning accuracy of a seabed mining vehicle not only directly affects the efficiency of aggregation, but also affects the reliability and stability of mining operations. In order to determine the noise reduction filtering algorithm, Which is most suitable for state estimation and position estimation models in mining vehicle sea trials, an Adaptive Kalman Filter (AKF) based on linear self-navigation position estimation is first proposed under an ideal Gaussian noise model and compared With conventional Kalman filter (KF) and Innovation Kalman filter (IKF) algorithms. Secondly, based on the underwater projection observatory, a nonlinear position estimation model based on distance and angle is proposed, introducing Gaussian noise. Particle Filter (PF) and improved particle filtering algorithms such as the Unscented Kalman Particle Filter(UPF), the Extended kalman Filter(EPF) are used for state estimation. The simulation results show that under the nonlinear position estimation model, UPF not only solves the problem of conventional Particle Filter (PF) divergence, but also significantly improves the accuracy of position estimation compared to self-navigation position estimation. The UPF algorithm based on an underwater projection observatory is best suited for navigational positioning of polymetallic nodule seabed mining vehicles.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114441245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Tracking and Speed Estimation of Ground Vehicles Using Aerial-view Videos 基于鸟瞰视频的地面车辆跟踪与速度估计

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230274

Dongyang Zhao, Yuqing Chen, Shuanghe Yu

引用次数: 3

Research on Target State Estimation and Terminal Guidance Algorithm in the Process of Multi-UAV Cooperative Attack 多无人机协同攻击过程中目标状态估计与末制导算法研究

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9229963

Zhongnan Tang, Yujie Wang, Qing-yang Chen, Xixiang Yang

{"title":"Research on Target State Estimation and Terminal Guidance Algorithm in the Process of Multi-UAV Cooperative Attack","authors":"Zhongnan Tang, Yujie Wang, Qing-yang Chen, Xixiang Yang","doi":"10.1109/CACRE50138.2020.9229963","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9229963","url":null,"abstract":"In order to achieve the cooperative attack of multi-UAV on targets (including static targets and moving targets), the process is divided into two stages, i.e. cruise stage and strike stage; the motion model of multi-UAV and targets and the observation model of targets are established based on the two-dimensional plane simplification assumption. In the cruise phase, multi-UAV cooperative target state estimation is realized based on Unscented Kalman filter (UKF), and cooperative attack guidance law is established under multiple constraints (including time, attack angle, seeker field angle, etc.) at the strike stage. In this paper, the system simulation is carried out for stationary target and moving target respectively, and the effectiveness of the proposed algorithm and scheme is verified. The results show that the Multi-UAV bearing-only state estimation can converge rapidly, the target positioning accuracy is about 10 m, and the estimation accuracy of the target line of sight angle is about 0.1°; the multi constraint guidance law can effectively improve the cooperative combat performance of the UAV cluster, the time cooperative accuracy is about 0.3s, the attack angle cooperative accuracy is about 0.5°, and the miss distance is less than 1m.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127058294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Adaptive Control of Satellite Attitude Tracking Based on RBF Neural Network 基于RBF神经网络的卫星姿态跟踪自适应控制

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/cacre50138.2020.9229956

Shao-ting Yu, Cai-zhi Fan

引用次数: 0

Moving Target Tracking with Robot Based on Laser Range Finder 基于激光测距仪的机器人运动目标跟踪

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230271

Chenggang Lu, Jinxiang Wang, Xu Cui

引用次数: 0

Performance Evaluation of Main Steam Temperature Control System of Thermal Power Unit Based on Mahalanobis Distance 基于马氏距离的火电机组主蒸汽温度控制系统性能评价

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230075

B. Hu, Jianbo Xie, Yusheng He, Yinsong Wang, Pingyan Ma

{"title":"Performance Evaluation of Main Steam Temperature Control System of Thermal Power Unit Based on Mahalanobis Distance","authors":"B. Hu, Jianbo Xie, Yusheng He, Yinsong Wang, Pingyan Ma","doi":"10.1109/CACRE50138.2020.9230075","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230075","url":null,"abstract":"As the main parameter of thermal power unit, the measurement and control of main steam temperature play an important role in the safe and economic operation of power plant. In order to improve the control quality of main steam temperature control system of thermal power unit, this paper presents a performance evaluation method of main steam temperature control system of thermal power unit based on Mahalanobis distance. This method is based on the output data of leading steam temperature and main steam temperature. Firstly, the data set representing the best performance of the system is selected according to Hurst index, and the benchmark of performance evaluation is established based on this data. Then the calculation process of traditional Mahalanobis distance is improved, and the specific calculation method of performance evaluation index based on the combination of Hurst index and improved Mahalanobis distance is given. Finally, the performance evaluation index is classified by membership function. The simulation results show that the evaluation method is effective and reasonable and the calculation is simple.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124169037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on Air Defense Communication Network of Warship Formation Based on Particle Swarm optimization 基于粒子群优化的舰艇编队防空通信网络研究

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230063

Peng-fei Peng, Pu Li, Yu Liu

{"title":"Research on Air Defense Communication Network of Warship Formation Based on Particle Swarm optimization","authors":"Peng-fei Peng, Pu Li, Yu Liu","doi":"10.1109/CACRE50138.2020.9230063","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230063","url":null,"abstract":"Aiming at the problem that the naval fleet air defense communication network survivability needs to be improved urgently, a network survivability evaluation function based on Natural Connectivity and Node Degree Uniformity Coefficient is established. This function not only inherits the advantages of simple expression of Natural Connectivity and fast calculation speed, but also has the ability to evaluate the network with uneven node distribution, which can significantly improve the accuracy of the evaluation of survivability. On this basis, combined with the basic idea of particle swarm optimization, the algorithm of air defense communication network of warship formation based on particle swarm optimization is proposed. The simulation results show that the improved network survivability evaluation function and particle swarm optimization based air defense communication networking algorithm can effectively improve the network survivability of real-time mobile communication networking, and have a good application in air defense communication networking optimization of naval ship formation in future complex battlefield environment.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121827492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Wavefront sensorless aberration correction utilizing SPGD algorithm with adaptive coefficient for laser scanning confocal microscopy 基于自适应系数SPGD算法的激光扫描共聚焦显微镜无波前像差校正

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9229951

Tianyu Zhang, Zhizheng Wu, Xiang Wei, Feng Li, Jialiang Wu, Kongbin Zhu

{"title":"Wavefront sensorless aberration correction utilizing SPGD algorithm with adaptive coefficient for laser scanning confocal microscopy","authors":"Tianyu Zhang, Zhizheng Wu, Xiang Wei, Feng Li, Jialiang Wu, Kongbin Zhu","doi":"10.1109/CACRE50138.2020.9229951","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9229951","url":null,"abstract":"Laser scanning confocal microscopy (LSCM) has become a common method for biological observation and medical science. Compared with traditional optical microscope, LSCM has the advantages of high contrast and three-dimensional (3D) imaging. However, with the increase of image depth, the resolution and contrast will be reduced due to the complexity of biological tissue aberrations. Adaptive optics system is an effective method to eliminate aberration. In this paper, a wavefront sensorless adaptive optics system is used to correct aberrations generated by complex refractive index of biological tissue. In order to increase the convergence speed and reduce the influence of photobleaching, an improved stochastic parallel gradient descent algorithm with adaptive coefficient is used to control the AO system. The optical path is simulated in ZEMAX and the feasibility of the proposed algorithm is verified in MATLAB. All simulation results demonstrate that the optimal algorithm can correct the aberration effectively with the designed optical system.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122167515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Surface Fitting Convolution for 3D Point Cloud Analysis 三维点云分析的自适应曲面拟合卷积

2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2020-09-01 DOI: 10.1109/CACRE50138.2020.9230294

Hezhi Cao, Yanxin Ma, Ronghui Zhan, Chao Ma, Jun Zhang

{"title":"Adaptive Surface Fitting Convolution for 3D Point Cloud Analysis","authors":"Hezhi Cao, Yanxin Ma, Ronghui Zhan, Chao Ma, Jun Zhang","doi":"10.1109/CACRE50138.2020.9230294","DOIUrl":"https://doi.org/10.1109/CACRE50138.2020.9230294","url":null,"abstract":"Traditional Convolutional Neural Networks (CNN) are limited to extract informative local features of point clouds due to the fixed geometric structures in convolution kernel against irregular and unstructured point clouds. It usually requires data transformation such as voxelization or projection, inducing a possible loss of information. Instead of fitting the input points to the kernel by regularization, we choose to fit the kernel to input points to conduct convolution. In this paper, we present a new method to define and compute convolution directly on 3D point clouds by Adaptive Surface Fitting Convolution (ASFConv). The key idea is to utilize a set of kernel points distributed on the tangent plane and project them back to point cloud surface. After adapting to the distribution of input points, ASFConv kernel can better capture local neighborhood geometry and benefit the feature extraction. In the experiments, we evaluate our network on two public datasets: ModelNet40 and ShapeNet for classification and segmentation. The experimental results show that our method obtain competitive performances compared to the state-of-the-art.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114629126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0