基于FastSLAM 2.0的二维室内定位与制图研究

2016 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC) Pub Date : 2016-09-01 DOI:10.1109/ICCEREC.2016.7814991

Dwi Kumiawan, A. N. Jati, U. Sunarya

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引用次数: 1

摘要

FastSLAM 2.0是一个同时定位和映射(SLAM)框架，它提供了一种算法来计算机器人的姿态和同时映射环境。它包括从传感器获取数据、关联数据和更新地图的计算。SLAM在机器人技术中是一个具有挑战性的问题，因为它被认为是一个先有鸡还是先有蛋的问题。本文将研究FastSLAM 2.0算法，该算法将使用RANSAC (Random Sampling Consensus)进行特征提取。

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A study of 2D indoor localization and mapping using FastSLAM 2.0

FastSLAM 2.0 is a Simultaneous Localization And Mapping (SLAM) framework that provides an algorithm for calculating robot's pose and map the environment concurrently. It consists of calculation that include getting data from sensor, associate the data, and update the map. SLAM is a challenging problem in Robotics because it is considered a chicken-and-egg problem. In this paper, ite will be studied the FastSLAM 2.0 algorithm that will be using RANSAC (Random Sampling Consensus) for its feature extraction.

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2016 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)

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