Automatic control of navigation system for robot

This paper will introduce the principle of autonomous navigation system. The main parts are scan matching, gmapping, frontier exploration, avoiding obstacles. The method and algorithm of scan matching specific are introduced in this paper. The mathematical model applied in field of scan matching can...

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Main Author: Zhang, Xue
Other Authors: Wang Han
Format: Final Year Project
Language:English
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/10356/60592
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-605922023-07-07T17:54:08Z Automatic control of navigation system for robot Zhang, Xue Wang Han School of Electrical and Electronic Engineering DRNTU::Engineering This paper will introduce the principle of autonomous navigation system. The main parts are scan matching, gmapping, frontier exploration, avoiding obstacles. The method and algorithm of scan matching specific are introduced in this paper. The mathematical model applied in field of scan matching can be four kinds. They are senor model, probabilistic model, original map model, ICP (Iterated Closest Point) method. And the SLAM (Simultaneous Localization and Mapping) is main algorithm applied in gmapping. I provide the detailed information on the building of partial map and whole map. And frontier exploration is a process of extending map. Terrain classification with different color is crux application in the frontier exploration. At last the part of avoiding obstacles is the key link in the autonomous navigation system. Kinematics equation applied in the avoiding obstacles is the crux method. And the protection distance always can effective avoid the hitting obstacles. I refer to the basic principle and method of the predecessor and turn theories into the practical. The experimental result achieves the goal of autonomous navigation and building current map. Bachelor of Engineering 2014-05-29T01:45:48Z 2014-05-29T01:45:48Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/60592 en Nanyang Technological University 59 p. application/msword
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Zhang, Xue
Automatic control of navigation system for robot
description This paper will introduce the principle of autonomous navigation system. The main parts are scan matching, gmapping, frontier exploration, avoiding obstacles. The method and algorithm of scan matching specific are introduced in this paper. The mathematical model applied in field of scan matching can be four kinds. They are senor model, probabilistic model, original map model, ICP (Iterated Closest Point) method. And the SLAM (Simultaneous Localization and Mapping) is main algorithm applied in gmapping. I provide the detailed information on the building of partial map and whole map. And frontier exploration is a process of extending map. Terrain classification with different color is crux application in the frontier exploration. At last the part of avoiding obstacles is the key link in the autonomous navigation system. Kinematics equation applied in the avoiding obstacles is the crux method. And the protection distance always can effective avoid the hitting obstacles. I refer to the basic principle and method of the predecessor and turn theories into the practical. The experimental result achieves the goal of autonomous navigation and building current map.
author2 Wang Han
author_facet Wang Han
Zhang, Xue
format Final Year Project
author Zhang, Xue
author_sort Zhang, Xue
title Automatic control of navigation system for robot
title_short Automatic control of navigation system for robot
title_full Automatic control of navigation system for robot
title_fullStr Automatic control of navigation system for robot
title_full_unstemmed Automatic control of navigation system for robot
title_sort automatic control of navigation system for robot
publishDate 2014
url http://hdl.handle.net/10356/60592
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