有色过程噪声下的轮式机器人同步定位与地图构建  

Colored-State-Noise Simultaneous Localization and Map Building for Wheel Robots

作　　者：弋英民[1] 刘丁[1] 

机构地区：[1]西安理工大学自动化与信息工程学院,陕西西安710048

出　　处：《电子学报》2010年第6期1339-1343,共5页Acta Electronica Sinica

基　　金：国家自然科学基金(No.60675048);陕西省教育厅自然基金(No.08JK385);西安市创新计划(No.YF07021)

摘　　要：由于机械制造工艺的原因,轮式机器人内部传感器获得的控制量在实际中为有色噪声,经典的同步定位与地图构建(SLAM)算法将不适用.提出一种有色过程噪声的机器人同步定位与地图构建算法.将机器人非线性过程模型线性化,用增广状态变量维数的方法将有色过程噪声模型转化为高斯白噪声模型.算法按照预测、观测、数据关联、更新、地图构建递推进行同步定位与地图构建.仿真结果表明,在有色过程噪声条件下,与EKF-SLAM算法和Fast-SLAM算法相比,提出的算法的机器人定位精度更好.Since the control state of wheel robots from encoder is colored noise in the mechanical manufacture,the traditional simultaneous localization and map building algorithms are on longer applicable.In the paper,an algorithm of colored-state-noise SLAM is proposed.Nonlinear process model is linearized and colored-state-noise model is converted into Gauss white noise one by augmenting dimension of state.The integral algorithm procedure follows the recursive order of prediction,observation,data association,update,mapping to have simultaneous localization and map building.MonteCarlo simulation results show that the proposed algorithm has higher estimate precision than those of EKF-SLAM algorithm and Fast-SLAM algorithm in colored process noise covariance.

关 键 词：有色噪声 轮式机器人 同步定位与地图构建(SLAM) 估计精度 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]