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浏览/检索结果: 共3条，第1-3条 帮助 已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择发表日期升序发表日期降序作者升序作者降序提交时间升序提交时间降序题名升序题名降序 Fuzzy Behavior-based Control of Three Wheeled Omnidirectional Mobile Robot 期刊论文 International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 2, 页码: 163-185 作者:  Nacer Hacene;  Boubekeur Mendil 收藏  |  浏览/下载：12/0  |  提交时间：2021/02/22 Three wheeled omnidirectional mobile robot (TWOMR)  autonomous navigation  obstacle avoidance  fuzzy behavior-based control  dynamic target  dynamic environment.   Design and test of focusing mechanism of space camera (EI CONFERENCE) 会议论文 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Design, Manufacturing, and Testing of Micro- and Nano-Optical Devices and Systems, April 26, 2010 - April 29, 2010, Dalian, China Guo Q.; Jin G.; Dong J.; Li Y.; Li W.; Wang H. 收藏  |  浏览/下载：22/0  |  提交时间：2013/03/25 According to the focal depth and work environment of a space camera  a focusing mechanism is designed  which consists of precision screw ball transmission and linear bearing guidance and accuracy improving. The dynamic- strike- resistance  adaptability to temperature and vacuum are considered into the reliable design method. Furthermore  the linearity error  the structure stability and the mechanism work situation in high and low temperature are tested. The result is that the linearity error of the mechanism is less than 0.003 mm  and the sway error of vertical way and level way of the mirror is less than 20''. The linearity error of the mechanism and the sway error of the mirror remain unchanged after vibration test. The mechanism can work in the complex space environment. 2010 SPIE.   A segment detection method based on improved Hough transform (EI CONFERENCE) 会议论文 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China Han Q.-L.; Zhu M.; Yao Z.-J. 收藏  |  浏览/下载：19/0  |  提交时间：2013/03/25 Hough transform is recognized as a powerful tool in shape analysis which gives good results even in the presence of noise and the disconnection of edge. However  3. applying the standard Hough transform equation to every point of the input image edge  4. according to the local threshold  6. merging the segments whose extreme points are near. Experiment results show the approach not only can recognize regular geometric object but also can extract the segment feature of real targets in complex environment. So the proposed method can be used in the target detection of complicated scenes  traditional Hough transform can only detect the lines  2. quantizing the parameter space  and extracting a group of maximums according to the global threshold  eliminating spurious peaks which are caused by the spreading effects  and will improve the precision of tracking.  cannot give the endpoints and length of the line segments and it is vulnerable to the quantization errors. Based on the analysis of its limitations  Hough transform has been improved in order to detect line segment feature of targets. The algorithm aims to avoid the loss of spatial information  as well as to eliminate the spurious peaks and fix on the line segments endpoints accurately  5. fixing on the endpoints of the segments according to the dynamic clustering rule  which can expediently be used for the description and classification of regular objects. The method consists of 6 steps: 1. setting up the image  parameter and line-segment spaces