期刊文献+

基于神经网络的多传感器信息融合技术在移动机器人中的应用 被引量:6

Neural network based multi-sensor data fusion in the mobile robots
在线阅读 下载PDF
导出
摘要 基于模糊神经网络的多传感器信息融合,提出了一种简单、有效的分区算法来确定障碍物的距离和方位。采用BP神经网络对障碍物环境进行分类以及模式识别,为移动机器人的导航和避障提供了一种有效的方法。 Based on neural network multi-sensor fusion date fusion, we put forward a simple sub-area arithmetic to fix the distance and position of obstacles. BP neutral network is used to classify the environment class and mode identification. The method offers a good way for the mobile robots to guide and positioning.
出处 《长春工业大学学报》 CAS 2008年第5期550-555,共6页 Journal of Changchun University of Technology
基金 国家863项目(2005AA4202301)
关键词 可移动机器人 多传感器信息融合 神经网络 mobile robot multi-sensor data fusion neural networks.
  • 相关文献

参考文献7

二级参考文献53

  • 1Quah K H, Quek H C, Leedham C G. Pattern classification using a fuzzy adaptive learning control network and reinforcement learning[A]. 9th International Conference on Neural Information Processing[C]. Singapore: November, 2002. 18-22.
  • 2Motoyuki Takai, Teruo Fujii, Tamaki Ura. A model based diagnosis system for autonomous underwater vehicles using artifical neural networks [A]. Proceeding of the 9th International Symposium on UUST[C], Durham,New Hampshire, 1995. 243-252.
  • 3Wang Y J, Zhang M J. Study of model of fuzzy neural networks applied to system condition monitoring[J]. Journal of Marine Science and Application, 2003, 1 (2).
  • 4Waltz E,Lilnas J.Multisensor data fusion [M].Boston:Artech House,2000.9-17.
  • 5Waltz E,Buede D M.Data fusion and decision support for command and control[J].IEEE Trans on Syst,Man & Cybern,1986,16 (6):865-879.
  • 6HallD L,Llinas J.An Introduction to Multisensor Data Fusion [J].Proc IEEE,2004,85(1):6-23.
  • 7Sasiadek J Z.Sensor fusion[J].Annual Reviews in Control,2002,26(26):203-228.
  • 8Halld L.Mathematical technique in multi-sensor data fusion [M].London:Artech House,2000.15-21.
  • 9Richard T.Principles of effective multisensor data fusion [J].Military Technology,2003,27(5):29-37.
  • 10Gao J B,Harris C J.Some remarks on Kalman filters for the multisensor fusion [J].Information Fusion,2002,3(3):191-201.

共引文献99

同被引文献48

引证文献6

二级引证文献16

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部