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Received:March 02, 2011 Revised:March 28, 2011
Received:March 02, 2011 Revised:March 28, 2011
中文摘要: 在复杂的不确定环境里,采用单一传感器对机器人进行定位时精度较低,并且易受干扰,可靠性较差。针对这一问题在粒子滤波器移动机器人SLAM 算法的基础上,利用多传感器融合对算法进行改进,将观测信息进行特征级融合,充分利用各种传感器采集的冗余信息,并将融合后的观测信息分别用来估计机器人路径和环境特征的后验概率分布。仿真试验表明,改进后的算法在SLAM 定位精度及可靠性上都有较大的提高,证明了该种方法的可行性。
Abstract:In a complex and uncertain environment, using a single sensor on the robot localization is poor in accuracy and reliability, and susceptible to the interference. For this problem, the mobile robot SLAM algorithm based on the particle filter is improved for use of multi-sensor fusion algorithm. The new algorithm fuses observe information on the feature level to take advantage of redundant information collected by various sensors, and the fusion information of observations were used to estimate the posterior probability distribution of robot path and the environmental characteristics. The simulation results show that the improved algorithm in accuracy and reliability of SLAM has greatly improved, and demonstrated the feasibility of the methods.
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唐骥锋,刘国栋.多传感器融合改进的机器人定位决策.计算机系统应用,2011,20(10):120-124
TANG Ji-Feng,LIU Guo-Dong.Improved Robots Localization Decisions Based on Multi-Sensor Fusion.COMPUTER SYSTEMS APPLICATIONS,2011,20(10):120-124
唐骥锋,刘国栋.多传感器融合改进的机器人定位决策.计算机系统应用,2011,20(10):120-124
TANG Ji-Feng,LIU Guo-Dong.Improved Robots Localization Decisions Based on Multi-Sensor Fusion.COMPUTER SYSTEMS APPLICATIONS,2011,20(10):120-124