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检索条件"机构=Key Laboratory of Complex System Intelligent Control"

共 6241 条记录，以下是4961-4970 订阅

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LiDAR-Based Initial Global Localization Using Two-Dimensional (2D) Submap Projection Image (SPI)

LiDAR-Based Initial Global Localization Using Two-Dimensiona...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Yanhao Li Hao Li École d’Ingénieurs SJTU-ParisTech (SPEIT) Shanghai China Shanghai Jiao Tong University (SJTU) Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

Initial global localization is important to mobile robotics in terms of navigation initialization (or re-initialization) and loop closure in SLAM. 3D LiDARs are commonly used for mobile robotics, yet LiDAR-based initial global localization (especially at large scale such as in outdoor environments) is still challenging due to lack of salient features in LiDAR range data. Inspired by visual SLAM oriented initial global localization methods, we propose a method of LiDAR-based initial global localization using 2D submap projection image (SPI). For this, global descriptors from SPIs are extracted for place recognition; pose estimation is realized by feature point matching between the queried SPI and SPIs from a global map database. The proposed initial global localization module runs at 2.4 Hz with precision of 1.2 m and for translation and 1.2° for rotation, which can serve as a suitable initial estimate for subsequent pose estimation refinement via existing mature point cloud registration methods.

关键词： Location awareness Visualization Laser radar Simultaneous localization and mapping Three-dimensional displays Pose estimation Two dimensional displays

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Reform of Computer Teaching for Practical Application

Reform of Computer Teaching for Practical Application

引用

作者： Li Huang Kai Zhang Wei Hu Mingchao Yu College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology

In view of the rapid development of contemporary computer technology, the problems that can be solved by computer technology are more and more complicated. Therefore, it is required that contemporary college students need to master certain computer operation skills and basic application skills of computer software combined with their professional knowledge before they officially enter the society. In this context, aiming at the computer-based teaching mode of non-computer majors in colleges and universities, the author analyzes the current situation of computer basic teaching in colleges and universities through his many years of teaching experience, and discusses the shortcomings in the development of computer courses in colleges and universities. Based on the degree of social requirements for contemporary college students to master computer technology, how to make university computer teaching cater to the continuous development and progress of computer science and technology, combined with the future computer skills of undergraduate students, the author puts forward some computer teaching reform opinions.

关键词： Computer foundation Teaching mode Application ability

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Improved target tracking based on spatio-temporal learning

Improved target tracking based on spatio-temporal learning

引用

International Conference on Information and Automation (ICIA)

作者： Songmin Jia Dishi Zeng Tao Xu Hui Zhang Xiuzhi Li College of Electronic and Control Engineering Beijing University of Technology Beijing China Ministry of Education Engineering Research Center of Digital Community Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (纸本)9781509041039

Object tracking is always in the core status with the develop of robotics. In this paper, we proposed a novel tracking framework based on Spatio-Temporal Context tracking (STC) and Template-Matching algorithm(TM). STC tracking method is a fast and simplified tracking method that strongly dependent on the context region (the surrounding background of the target). Therefore, it cannot correct the tracking error by itself and even lost the target during tracking. Under this circumstance, we make a closed-loop judgment whether the movement of the target between two neighboring image sequence larger than a constant or not. If the movement larger than the constant, the template matching is employed as sample detector to correct the error or re-track the target on line. The template-matching algorithm is an efficient and fast detection algorithm that find the maximum probability point in the image that similar to the template. In order to decrease the calculating time, the search region is not the whole image but the context region of STC tracking method. What's more, after tracking and detecting we update the scale parameter to adapt the change of the target's appearance. Finally, experimental result demonstrate that our tracking method have improve the robustness of tracking.

关键词： Target tracking Context Context modeling Computational modeling Robustness Mathematical model

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Simulation Testing of Large-Scale Grid-Connected Wind Power with Energy Storage system Based on Active Support Performance Evaluation Indices

Simulation Testing of Large-Scale Grid-Connected Wind Power ...

引用

Electrical Engineering and Automation (IFEEA), International Forum on

作者： Yihua Zhu Yun Hu Liang Tu Mingzhang Su Chao Luo State Key Laboratory of HVDC Electric Power Research Institute CSG Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

This paper establishes simulation modeling for large-scale grid connected wind power with energy storage system (ESS). The conventional grid-following (GFL) based ESS is used as a reference object to test the active support performance of large-scale grid-connected wind power with grid-forming (GFM) based ESS with active support performance evaluation indices in different scenarios. (1) Small disturbance evaluation indices: The point of common coupling (PCC) frequency/voltage drop depth and recovery time. (2) Large disturbance evaluation indices: The PCC frequency/voltage drop depth and rise height after fault removal. The output active/reactive power drop depth and rise height/recovery time after fault removal. (3) Island capability evaluation indices: The PCC frequency/voltage fluctuation amplitude at the moment of switching and system stability after switching.

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Optimal Consensus control of Unknown Nonlinear Multi-Agent systems Using Adaptive Dynamic Programming via MRAC

Optimal Consensus Control of Unknown Nonlinear Multi-Agent S...

引用

Chinese control Conference (CCC)

作者： Hao Fu Xin Chen Wei Wang Jinbin Li Yaodong Zhang Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China State Grid Hubei Electric Power Research Institute Wuhan P. R. China

This paper introduces an optimal consensus control scheme for nonlinear multi-agent systems with completely unknown dynamics. In general, it is difficult to solve the coupled Hamilton-Jacobi-Bellman (HJB) equations, which the optimal consensus control relies on in multi-agent systems, especially unknown nonlinear systems. For the purpose of solving the problem, we propose an optimal consensus control approach based on the model reference adaptive control (MRAC) and adaptive dynamic programming (ADP). Using the structure of the diagonal recurrent neural network, the identifier and controller are devised to achieve MRAC for every plant of the unknown nonlinear systems, i.e. the reference model serves as a dynamic model of each individual agent. Then, according to reference models of distributed agents, an adaptive dynamic programming (ADP) is introduced to approximate the solution of the coupled HJB equations.

关键词： Multi-agent systems Mathematical model Adaptation models Heuristic algorithms Recurrent neural networks Dynamic programming

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Step-length optimization based on genetic algorithm for a parallel mobile robot

Step-length optimization based on genetic algorithm for a pa...

引用

International Conference on Information Science and control Engineering (ICISCE)

作者： Shuang Liu Wei Chen Hang Wu Wenchang Zhang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Tianjin University of Technology Tianjin China Academy of Military Sciences of Chinese PLA Institute of Medical Support Technology Tianjin China

With the development of technology, parallel mobile robots have been paid more attention in various industries due to the strong load capacity, high running stability and rapid response speed. However, step-length optimization is an important but challenging task for this kind of mobile robot. Step length has dramatic effect on the stability of robot and the performance of electric cylinder. Balancing the speed characteristics and stability margin, we propose a genetic algorithm to solve this problem and design a novel fitness function that can measure the motion characteristics of parallel mobile robot. Effectiveness of our method is verified by experiments.

关键词： Industries Information science control engineering Service robots Mobile robots Motion measurement Task analysis

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3D Deep Learning for 3D Printing of Tooth Model

3D Deep Learning for 3D Printing of Tooth Model

引用

IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Yiwen Liu Xiuqin Shang Zhen Shen Bin Hu Zhihai Wang Gang Xiong Faculty of Information The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing University of Technology Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China Faculty of Information Beijing University of Technology Beijing China

Recently, with the development of both 3D sensors and 3D virtual network that bring the needs of interaction with the real world, many 3D applications burst out. However, it is difficult to understanding these three-dimensional scenes with a fixed program. Then, a data-driven method is required to process these 3D data, which brings a strong demand of 3D Deep Learning in 3D data. Towards this goal, with an end-to-end deep learning, the experiment is based on PointNet++, a well proposed method for feature extraction. The experiment optimizes the network structure and parameters to improve the classification results. Finally, the network is applied to tooth model for classification and identification so that the dental model can be found from different perspectives.

关键词： Three-dimensional displays Deep learning Transforms Cameras Object segmentation Image segmentation Sensors

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Qualitative Elemental Analysis of Minerals Based on Energy Dispersive X - ray Fluorescence Spectrometry

Qualitative Elemental Analysis of Minerals Based on Energy D...

引用

Chinese control Conference (CCC)

作者： JunLei Song ZhiHeng Yang Jing Cai XiaoYong Ni DianHong Wang Xing Jin WenQin Mo KaiFeng Dong Fang Jin Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China School of Mechanical and Electronic Information china University of Geosciences Wuhan P. R. China

The research of miniaturized XRF/XRD analyzers are carried out in this paper, especially the qualitative analysis based on EDXRF, a miniaturized energy dispersive X-ray fluorescence spectrometry platform is designed and a qualitative elemental analysis software based on Android operating system is developed. The elemental qualitative analysis software can preprocess the X-ray feature spectrum by background eliminationsmoothing and energy coefficient calibration, after these pretreatments, the main elements of the sample can be analyzed. The experimental results show that the qualitative elemental analysis platform proposed in this paper can measure the elements of Al to Au in the periodic table, besides, the detection accuracy of multiple samples is higher than 97%. The mineral qualitative elemental analysis software proposed in this paper can be applied to any portable analysis platform based on Android operating system, moreover, it will spur advances in the development of the miniaturization and intelligent X-ray fluorescence spectrometer.

关键词： Minerals Software Calibration Spectroscopy Instruments Detectors Smoothing methods

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The application of TCSC for damping inter-area oscillations

The application of TCSC for damping inter-area oscillations

引用

IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Jingli Liu Lei Ding Deyu Cai Zhiming Song Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China Shanghai Electric Power Corporation Ltd Shanghai China State Grid of China Technology College Jinan China

ISBN: (纸本)9781467381338

This paper presents a wide area control scheme using TCSC for damping inter-area oscillation. In general, TCSC are facilitated over long transmission lines to enhance the power transmission capability. As the inter-area oscillations are associated with heavy power transfer over long transmission corridors, the small signal/oscillatory stability can be improved if an additional damping control can be integrated into the control scheme of TCSC. The paper presents the classic and additional damping control scheme of TCSC. The typical two-area power system and control scheme that are built using `DIgSILENT PowerFactory', and the damping control is tested through the classic modal analysis and simulations in time domain.

关键词： Power capacitors Thyristors Damping Oscillators Economic indicators Power system stability system performance

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Autonomous Exploration and Mapping for Mobile Robots via Cumulative Curriculum Reinforcement Learning

Autonomous Exploration and Mapping for Mobile Robots via Cum...

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IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Zhi Li Jinghao Xin Ning Li Department of Automation Shanghai Jiao Tong University Shanghai P.R. China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai China Shanghai Engi-neering Research Center of Intelligent Control and Management Shanghai China

Deep reinforcement learning (DRL) has been widely applied in autonomous exploration and mapping tasks, but often struggles with the challenges of sampling efficiency, poor adaptability to unknown map sizes, and slow simulation speed. To speed up convergence, we combine curriculum learning (CL) with DRL, and first propose a Cumulative Curriculum Reinforcement Learning (CCRL) training framework to alleviate the issue of catastrophic forgetting faced by general CL. Besides, we present a novel state representation, which considers a local egocentric map and a global exploration map resized to the fixed dimension, so as to flexibly adapt to environments with various sizes and shapes. Additionally, for facilitating the fast training of DRL models, we develop a lightweight grid-based simulator, which can substantially accelerate simulation compared to popular robot simulation platforms such as Gazebo. Based on the customized simulator, comprehensive experiments have been conducted, and the results show that the CCRL framework not only mitigates the catastrophic forgetting problem, but also improves the sample efficiency and generalization of DRL models, compared to general CL as well as without a curriculum. Our code is available at https://***/BeamanLi/CCRL_Exploration.

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