提出一种新的移动机器人全局定位与自主泊位方法.该方法分为两阶段:离线阶段,采用SIFT(Scale In-variant Feature Transform)算法并提出一种基于DD-BBF(Double Direction Best Bin First)的特征匹配方法实现视觉特征三维重建;将进化策...提出一种新的移动机器人全局定位与自主泊位方法.该方法分为两阶段:离线阶段,采用SIFT(Scale In-variant Feature Transform)算法并提出一种基于DD-BBF(Double Direction Best Bin First)的特征匹配方法实现视觉特征三维重建;将进化策略应用于Rao-Blackwellized粒子滤波器,并结合自适应重采样,实现了移动机器人同时定位和特征地图创建.在线阶段,采用基于HMM(Hidden Markov Model)的方法实现全局泊位位置识别;采用RANSAC算法实现全局度量定位;提出极点伺服控制方法,实现机器人精确自主泊位.在室内环境下的实验结果证实了该方法的优良性能.展开更多
The traditional geometrical depolarization model that single transmitter to single receiver provides a simple method of polarization channel modeling. It can obtain the geometrical depolarization effect of each path i...The traditional geometrical depolarization model that single transmitter to single receiver provides a simple method of polarization channel modeling. It can obtain the geometrical depolarization effect of each path if known the antenna configuration, the polarization field radiation pattern and the spatial distribution of scatters. With the development of communication technology, information transmission spectrum is more and more scarce. The original model provides only a single channel polarization state, so the information will be limited that the polarization state carries in the polarization modulation. The research is so significance that how to carries polarization modulation information by using multi-antenna polarization state. However, the present study shows that have no depolarization effect model for multi-antenna systems. In this paper, we propose a multi-antenna geometrical depolarization model. On the basis of a single antenna to calculate the depolarization effect of the model, and through simulation to analysis the main factors that influence the depolarization effect. This article provides a multi-antenna geometrical depolarization channel modeling that can applied to large-scale array antenna, and to some extent increase the speed of information transmission.展开更多
文摘提出一种新的移动机器人全局定位与自主泊位方法.该方法分为两阶段:离线阶段,采用SIFT(Scale In-variant Feature Transform)算法并提出一种基于DD-BBF(Double Direction Best Bin First)的特征匹配方法实现视觉特征三维重建;将进化策略应用于Rao-Blackwellized粒子滤波器,并结合自适应重采样,实现了移动机器人同时定位和特征地图创建.在线阶段,采用基于HMM(Hidden Markov Model)的方法实现全局泊位位置识别;采用RANSAC算法实现全局度量定位;提出极点伺服控制方法,实现机器人精确自主泊位.在室内环境下的实验结果证实了该方法的优良性能.
基金supported in part by the National Natural Science Foundation of China(61561039,61461044)the Natural Science Foundation of Ningxia(NZ14045)the Higher School Science and Technology Research Project of Ningxia(NGY2014051)
文摘The traditional geometrical depolarization model that single transmitter to single receiver provides a simple method of polarization channel modeling. It can obtain the geometrical depolarization effect of each path if known the antenna configuration, the polarization field radiation pattern and the spatial distribution of scatters. With the development of communication technology, information transmission spectrum is more and more scarce. The original model provides only a single channel polarization state, so the information will be limited that the polarization state carries in the polarization modulation. The research is so significance that how to carries polarization modulation information by using multi-antenna polarization state. However, the present study shows that have no depolarization effect model for multi-antenna systems. In this paper, we propose a multi-antenna geometrical depolarization model. On the basis of a single antenna to calculate the depolarization effect of the model, and through simulation to analysis the main factors that influence the depolarization effect. This article provides a multi-antenna geometrical depolarization channel modeling that can applied to large-scale array antenna, and to some extent increase the speed of information transmission.
