中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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浏览/检索结果: 共16条,第1-10条 帮助

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Detecting and Tracking 6-DoF Motion of Unknown Dynamic Objects in Industrial Environments Using Stereo Visual Sensing 期刊论文  OAI收割
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2024, 页码: 13
作者:  
Cao, Hao
  |  收藏  |  浏览/下载:22/0  |  提交时间:2024/09/09
MOC: Wi-Fi FTM With Motion Observation Chain for Pervasive Indoor Positioning 期刊论文  OAI收割
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2024, 页码: 16
作者:  
Shao, Wenhua;  Luo, Haiyong;  Zhao, Fang;  Hong, Yunhan;  Li, Yaqi
  |  收藏  |  浏览/下载:8/0  |  提交时间:2024/12/06
An Adaptive Stacking-OF Method for Extracting Glacier Velocity Field Using Optical Remote Sensing Datasets 期刊论文  OAI收割
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2024, 卷号: 21, 页码: 5
作者:  
Fu, Yin;  Zhang, Bo;  Liu, Qiao;  Shi, Yue;  Wang, Jiao
  |  收藏  |  浏览/下载:6/0  |  提交时间:2024/12/04
Hierarchical Motion Learning for Goal-Oriented Movements With Speed-Accuracy Tradeoff of a Musculoskeletal System 期刊论文  OAI收割
IEEE TRANSACTIONS ON CYBERNETICS, 2021, 页码: 14
作者:  
Zhou, Junjie;  Zhong, Shanlin;  Wu, Wei
  |  收藏  |  浏览/下载:29/0  |  提交时间:2022/01/27
Optimal synthesis of pose repeatability for collaborative robots based on the ISO 9283 standard 期刊论文  OAI收割
Industrial Robot, 2019, 页码: 1-7
作者:  
Hu MW(胡明伟);  Wang HG(王洪光);  Pan XA(潘新安);  Tian Y(田勇)
  |  收藏  |  浏览/下载:35/0  |  提交时间:2019/09/15
Motion error based robust topology optimization for compliant mechanisms under material dispersion and uncertain forces 期刊论文  OAI收割
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2018, 卷号: 57, 期号: 6, 页码: 2161-2175
作者:  
Wang XJ
  |  收藏  |  浏览/下载:41/0  |  提交时间:2018/07/17
The application of digital signal processing (DSP) for the real time solving of artillery fire control exterior trajectory (EI CONFERENCE) 会议论文  OAI收割
2012 IEEE 3rd International Conference on Software Engineering and Service Science, ICSESS 2012, June 22, 2012 - June 24, 2012, Beijing, China
作者:  
Li D.
收藏  |  浏览/下载:141/0  |  提交时间:2013/03/25
Efficient human action recognition using accumulated motion image and support vector machines (EI CONFERENCE) 会议论文  OAI收割
International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2011, November 19, 2011 - November 23, 2011, Suzhou, China
作者:  
Zhang X.;  Zhang J.;  Zhang J.;  Zhang X.;  Zhang X.
收藏  |  浏览/下载:68/0  |  提交时间:2013/03/25
Vision-based human action recognition provides an advanced interface  and research in this field of human action recognition has been actively carried out. This paper describes a scheme for recognizing human actions from a video sequences. The proposed method is an extension of the Motion History Image(MHI) method based on the ordinal measure of accumulated motion  which is robust to variations of appearances. We define the accumulated motion image(AMI) using image differences firstly. Then the AMI of the video sequencesis resized to a MN regulation following the standard of training phases. Finally  we employ Support Vector Machine(SVM) as a classifier to distinguish the current activity in target video sequences. In a word  our proposed algorithm not only outperforms the state of art on public available KTH data set and Weizmann data set  but also proves practical to some real world applications  in addition  this method is computationally simple and able to achieve a satisfactory accuracy.  
Design and analysis of auto-focus assembly for spaceborne remote sensing camera (EI CONFERENCE) 会议论文  OAI收割
2011 International Conference on Electronics, Communications and Control, ICECC 2011, September 9, 2011 - September 11, 2011, Ningbo, China
作者:  
Chen W.;  Gao X.
收藏  |  浏览/下载:30/0  |  提交时间:2013/03/25
Spaceborne remote sensing camera may be out of focus when the environment and photographic distance changes. In order to get higher ground sampled distance for the camera  based on the experience gained from the development of a remote sensing camera  working principle of auto-focus assembly control system was discussed. Time of waveform extraction was reduced. It sets force an auto-focus assembly that uses cam and line guide rail in order to move the lens group. The motion error of the auto-focus assembly was difficult to be eliminated and would affect on the focusing accuracy of the spaceborne remote sensing camera directly. So it was analyzed at both ends of the focusing structure. The CCD detector can keep stable when the remote sensing camera is imaging. The motion error was tested to verify the validity of the simulation result and it is less than 0.01mm. Its accuracy meets using demand. The focusing method of moving focal plane is suitable for spaceborne remote sensing camera. 2011 IEEE.  
Three-sample rotation vector algorithm with angular rate input (EI CONFERENCE) 会议论文  OAI收割
2011 2nd International Conference on Mechanic Automation and Control Engineering, MACE 2011, July 15, 2011 - July 17, 2011, Inner Mongolia, China
作者:  
Zhang Y.
收藏  |  浏览/下载:22/0  |  提交时间:2013/03/25
In order to research the attitude algorithm with angular rate input under the conical motion  a optimal threesample rotation vector algorithm based on single-step Newton backward interpolation is proposed. Using the principle of limited rigid body rotation and the characteristic of angular rate input  three-sample rotation vector algorithm is derivated. To minimum attitude errors  three-sample rotation vector algorithm is optimized. Three angular rate extraction methods of singlestep entire sample recursion  multi-step entire sample and singlestep Newton backward interpolation are proposed. Under the condition of conical motion with semi-cone angle 3 and angular frequency 2rad/s  simulation is done. The simulation results show that single-step Newton backward interpolation is superior to the other two methods  and its maximum error peak is 0.01  error drift rate is 0.036/h. Experiments in three-axis flying turntable with the same parameters are carried out  and the results show that error drift rates of three-channels are less than those of traditional quaternion  which are 13.53%  12.08% and 23.68% lower respectively. It also verified that the new algorithm can perform a high accuracy under the conical motion. 2011 IEEE.