检索结果-内蒙古大学图书馆

Chinese Automation Congress

作者： Zhongming Ren Wenjing Li Junfei Qiao Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

Recently, Gravitational search algorithm (GSA) was considered as one method for optimizing functions and solving real problems. For the sake of better adjust the values of recurrent RBF neural network (RRBFNN) to make the network achieve better performance, the MGSA is essential in this article. The advised work achieves a better compromise between exploration and development. At the same time, by increasing the guidance of the global optimal particle, the problem that the gravitational search algorithm converges slowly in the later iteration is solved. The Experiment found that the network has better convergence speed and better test accuracy than the RRBFN optimized by the conventional optimization algorithm.

关键词： Gravitational search algorithm Recurrent RBF neural network Optimization Fast convergence speed

来源：评论

学校读者我要写书评

暂无评论

Balancing control of a cubical robot balancing on its corner

Balancing control of a cubical robot balancing on its corner

引用

International Workshop on Advanced Motion Control (AMC)

作者： Zhigang Chen Xiaogang Ruan Yuan Li Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

Aiming at the problem of balancing control of a cubical robot, this paper makes a research on the balancing control of a cubical robot balancing on its corner. Using the physical prototype of cubical robot we designed as the research object, the dynamic model is derived with Lagrangian method. A balancing controller is proposed base on a nonlinear control method - active disturbance rejection control (ADRC). There are three ADRC controllers in pitch, roll and yaw direction. The internal and external disturbance of the system are regarded as the total disturbances of the ADRC controller. The effectiveness of the controller is verified in the comparison with PID algorithm with the obtained expect effect. The controller developed can provide a base for further study for balancing control of a physical prototype cubical robot.

关键词： Mobile robots Wheels Robot kinematics Prototypes Regulators Robust control

来源：评论

学校读者我要写书评

暂无评论

Corrections to "Learning to Learn Adaptive Classifier-Predictor for Few-Shot Learning"

引用

IEEE transactions on neural networks and learning systems 2021年第8期32卷 3784页

作者： Nan Lai Meina Kan Chunrui Han Xingguang Song Shiguang Shan Key Laboratory of Intelligent Information Processing Institute of Computing Technology (ICT) Chinese Academy of Sciences (CAS) Beijing China University of Chinese Academy of Sciences Beijing China Huawei Technologies Company Ltd. Shenzhen China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai China

In the above article [1], the results of "Fully-supervised (Upper bound)" in Tables III and IV were inadvertently set to intermediate records that were used as placeholders. This error has no effect on any of the interpretations and conclusions. Tables I and II of this amendment show the corrected results (highlighted in italics) of the original Tables III and IV.

关键词： Predictive models Feature extraction Deep learning Learning systems Adaptive systems

来源：评论

学校读者我要写书评

暂无评论

Prediction of PM_(2.5) Concentration Based on NDFA-LSSVM Model

Prediction of PM_(2.5) Concentration Based on NDFA-LSSVM Mod...

引用

Chinese Automation Congress

作者： Jiangeng Li Jianing Shen Xiaoli Li Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

At present, there are widespread air pollution problems in most parts of China, the accurate prediction of atmospheric pollutant concentration has become a hot issue for people to study. This paper proposes the NDFA-LSSVM model to predict the concentration of PM_(2.5). The hyper-parameter of Least Square Support Vector Machine (LSSVM) were optimized by using the New Dynamic Firefly Algorithm (NDFA) to establish a PM_(2.5) concentration prediction model NDFA-LSSVM. The air quality data of monitoring stations at Chaoyang Agricultural Exhibition Hall District was used as source data to compare the performance of the optimized model with LSSVM model and General Regression Neural Network (GRNN) model. The experimental results show that the NDFA-LSSVM model proposed in this paper effectively improves the prediction accuracy of PM_(2.5) concentration.

关键词： PM_(2.5) NDFA-LSSVM Prediction model GRNN

来源：评论

学校读者我要写书评

暂无评论

Panorama video stitching system based on VR Works 360 video

Panorama video stitching system based on VR Works 360 video

引用

Chinese Automation Congress (CAC)

作者： Jiangeng Li Minjie Fan Guangsheng Wang Xiaoli Li Rihui Sun Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

As the vision captured by a single camera is limited, panoramic video technology has emerged. Panorama video is to synthesize a real-time video that can watch surrounding 360-degree scenes by taking multiple videos of surrounding scenes. This article builds on the VRWorks 360 video software development kit released by NVIDIA to build a real-time stitching system. Collect 4 channels of video stream with a resolution of 1920×1080 to produce a panoramic real-time video with a resolution of 4k. In the experiment, four module cameras are used to collect the video stream in real time. In the process of stitching, we fully combine the respective advantages of the CPU and the GPU, and use GPU to accelerate the real-time video stitching. Experimental results show that the stitching system can output high-quality panoramic video.

关键词： Streaming media Feature extraction Cameras Graphics processing units Real-time systems Acceleration Image registration

来源：评论

学校读者我要写书评

暂无评论

Dioxin Emission Concentration Soft Measuring Method Based on Selective Ensemble Least Square Support Vector Machine Algorithm

Dioxin Emission Concentration Soft Measuring Method Based on...

引用

Chinese Control Conference (CCC)

作者： Jian Tang Junfei Qiao Zihao Guo Aijun Yan Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

Dioxin (DXN) is a highly toxic and persistent pollutant discharged from municipal solid waste incineration (MSWI). The first principal model of DXN is difficult to establish due to the complex physical and chemical characteristics of the incineration process. In the practical process, DXN emission concentration is off-line detected with monthly or seasonal periods. Aim at such small sample modeling problem, a soft measuring method based on selective ensemble (SEN) least square support vector machine (LSSVM) for modeling DXN emission concentration is proposed. At first, candidate training sub-samples are produced from original training samples. Then, different candidate sub-sub-models based on the same kernel parameter and regularization parameter are constructed by using LSSVM. Thirdly, ensemble sub-models are selected by using the genetic algorithm optimization tool box and prior knowledge. Finally, these ensemble sub-models are combined by using partial least squares algorithm in terms of reduction con-linearity among different prediction outputs. Simulation results show effectiveness of the proposed approach by using dataset in reference [18].

关键词： Training Incineration Predictive models Data models Pollution measurement Genetic algorithms Support vector machines

来源：评论

学校读者我要写书评

暂无评论

An In-Motion Initial Alignment Algorithm for SINS Using Adaptive Lie Group Filter

An In-Motion Initial Alignment Algorithm for SINS Using Adap...

引用

Chinese Control Conference (CCC)

作者： Hao Xu Fujun Pei Ning Jiang Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

In this paper, an in-motion initial alignment algorithm based on Lie group is proposed, which effectively solves the non-uniqueness of the unit-quaternion attitude description and the nonlinear problem when using unit-quaternion for state estimation. The algorithm divides the attitude matrix into three successive special orthogonal matrices according to the property of the rotation on Lie group description and the basic principle of inertial navigation, and isolates the angular velocity and linear velocity of the carrier under dynamic conditions. Based on the mapping relation between Lie group and Lie algebra and the optimal estimation principle, and the uncertainty of measurement noise in modeling is analyzed, an adaptive Lie group filter method is proposed to estimate the initial inertial matrix directly. It can be seen from the experimental results that compare with the unit quaternion algorithm proposed algorithm has improved the alignment accuracy and stability. This method is an excellent situation to the SINS initial alignment in-motion.

关键词： Mathematical model Quaternions Noise measurement Navigation Earth Covariance matrices Algebra

来源：评论

学校读者我要写书评

暂无评论

Improved Autonomous Exploration Technology of Mobile Robot in Unknown Building Environments

Improved Autonomous Exploration Technology of Mobile Robot i...

引用

Chinese Automation Congress

作者： Songmin Jia Yalei He Xiuzhi Li Xiangyin Zhang Mingai Li Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

This paper addresses the issues of the autonomous exploration and grid-topology hybrid map building of mobile robots in large-scale environments. First, in order to improve the defect of the original method in the special environment, a way to extract the target point based on the free area is proposed. Then, we use the information gain and the extraction method of fast back to the initial topological node to evaluate the target point, so as to solve the problem that the long time no loop closure detection leads to the failure of the map building. Finally, we propose an improved method of building and optimizing the real-time topological map based on the information of the laser data and grid map, which makes the grid-topology hybrid map more concise and the exploration process more efficient. The effectiveness of the proposed autonomous exploration and grid-topology hybrid map building method for mobile robots in unknown environments is verified by experiments.

关键词： Map building Mobile robot Target point extraction Autonomous exploration

来源：评论

学校读者我要写书评

暂无评论

Dynamic obstacle tracking based on high-definition map in urban scene

Dynamic obstacle tracking based on high-definition map in ur...

引用

2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Li, Yuxiao Wang, Can Su, Zhilong Duan, Shengcai Wu, Xinyu Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen518055 China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Beijing100049 China Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781728163215

The application of High-Definition map can realize centimeter-level position in urban scenes, the development of deep learning has made great breakthrough in the point cloud dynamic obstacle recognition. All these technologies make obstacle detection and tracking based on High-Definition map effectively realize in the modern smart city scene. It is different from the previous obstacle detection and tracking methods based purely on vision the using of High-Definition map can provide high-precision positioning and reduce the difficulty of point cloud classification. The using of lidar also solves the problem of up-to-scale in dynamic detection. In this paper, we put forward a new Multi-camera Lidar Point Cloud Map, we complete the map at normal speed on the highway and get a satisfactory result. At the same time, we also find a robust combination of traditional kalman filter, Hungary algorithm and current deep learning to solve dynamic obstacle tracking and detection. The experimental results show that our system can effectively complete the special problem of generating map and target tracking on urban scene. © 2019 IEEE.

关键词： Optical radar

来源：评论

学校读者我要写书评

暂无评论

Application of three-dimensional vision perception technology to industrial robots

引用

Journal of Physics: Conference Series 2021年第1期2082卷

作者： Rui Yang Qinglong Mo Yuhong Li Lin Gan Ruihan Hu Guangdong Institute of Intelligent Manufacturing Guangdong Key Laboratory of Modern Control Technology Guangzhou 510070 China Cloud Computing Center Chinese Academy of Sciences Dongguan 523808 china Guangdong Key Laboratory of Modern Control Technology Guangdong Institute of Intelligent Manufacturing Guangzhou China Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Beijing China Xinjiang Production and Construction Corps Key Laboratory of Modern Agricultural Machinery Shihezi University Shihezi China

The three-dimensional vision system can improve the active perception ability of the robot, and then guide its flexible operation. This system has been widely used in industrial production processes, such as disorderly sorting, assembly, flexible welding, and defect detection. In sorting, assembly and other applications, accurate perception in a complex and changeable industrial environment is essential. Moreover, the control and other operations should be completed under the guidance of feedback information based on the collected three-dimensional perception results. Nonetheless, improvements are still required, such as accurate three-dimensional detection and positioning of work-in-progress and autonomous guidance in a complicated industrial context with continuous changes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：