Approach of simultaneous localization and mapping based on local maps for robot

被引：7

作者：

陈白帆 ^{[1
]}

蔡自兴 ^{[1
]}

胡德文 ^{[2
]}

机构：

[1] School of Information Science and Engineering, Central South University

[2] College of Mechatronics and Automation, National University of Defense Technology

来源：

Journal of Central South University of Technology(English Edition) | 2006年 / 06期

关键词：

simultaneous localization and mapping; extended Kalman filter; local map;

D O I：

暂无

中图分类号：

TP242 [机器人];

学科分类号：

1111 ;

摘要：

An extended Kalman filter approach of simultaneous localization and mapping(SLAM) was proposed based on local maps. A local frame of reference was established periodically at the position of the robot, and then the observations of the robot and landmarks were fused into the global frame of reference. Because of the independence of the local map, the approach does not cumulate the estimate and calculation errors which are produced by SLAM using Kalman filter directly. At the same time, it reduces the computational complexity. This method is proven correct and feasible in simulation experiments.

引用

页码：713 / 716

页数：4