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西安交通大学 [1]
长春光学精密机械与物... [1]
沈阳自动化研究所 [1]
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会议论文 [2]
期刊论文 [1]
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2013 [1]
2011 [1]
2008 [1]
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Three-dimensional modeling of simulation scene in campus navigation system
期刊论文
Journal of Chemical and Pharmaceutical Research, 2013, 卷号: 5, 期号: 12, 页码: 103-107
作者:
Qin LJ(秦丽娟)
;
Li, Ying
;
Yao C(姚辰)
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浏览/下载:16/0
  |  
提交时间:2014/05/14
Three-dimensional Modeling
Campus navigation
Simulation scene
Texture
Poly-X: An online intelligent tutoring system for e-learning
会议论文
作者:
Liu, James N.K
;
Shiu, Simon
;
Wang, Yuan
;
Li, Zunchao
;
Jia, Liwei
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浏览/下载:3/0
  |  
提交时间:2019/12/10
Adaptive navigation
Communication platforms
Group discussions
Independent learning
Intelligent tutoring system
Off-campus students
Teaching-learning activities
Web based e learning
Platform and steady kalman state observer design for intelligent vehicle based on visual guidance (EI CONFERENCE)
会议论文
2008 IEEE International Conference on Industrial Technology, IEEE ICIT 2008, April 21, 2008 - April 24, 2008, Chengdu, China
Rong-hui Z.
;
Rong-ben W.
;
Feng Y.
;
Hong-guang J.
;
Tao C.
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浏览/下载:20/0
  |  
提交时间:2013/03/25
State observer design is one of key technologies in research field of intelligent vehicle. Experiment platform
visual guidance intelligent vehicle JLUIV-5
is establishedby Jilin University Intelligent Vehicle Group firstly. The system structure and assistant navigation control system
and different image identify algorithms to recognize preview path and stops for variable illuminations are introduced. The dynamic response equation of steering control system was got by system identification experiment. By combined with the preview kinematics model
and two-degree steering dynamic model of vehicle
the steering kalman filter mathematics model based on preview kinematics for intelligent vehicle was obtained. And observer is designed by applying steady Kalman filter theory. The simulation and experiment results
carry out in Jilin University Nanling Campus and Culture Center of Jilin Province
show that the image identify algorithms
and steady Kalmanstate observer designed by the proposed method has good adaptability for time-varying and parameters uncertain
it can satisfy intelligent vehicle trace the path reliably during outdoor experiment. 2008 IEEE.
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