Grid-based simultaneous localization and mapping using Rao-blackwellized particle filter with neural network for mini robots / Norhidayah Mohamad Yatim
Mini robots can be used in many applications such as in domestic, industrial or humanitarian fields. Typically, mini robot platforms are equipped with sparse and noisy sensors on board such as array of infrared sensors. In robotics, the ability to map the surrounding area and determine self-location...
Saved in:
Main Author: | |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2018
|
Subjects: | |
Online Access: | https://ir.uitm.edu.my/id/eprint/82558/1/82558.pdf https://ir.uitm.edu.my/id/eprint/82558/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.uitm.ir.82558 |
---|---|
record_format |
eprints |
spelling |
my.uitm.ir.825582024-03-07T08:39:33Z https://ir.uitm.edu.my/id/eprint/82558/ Grid-based simultaneous localization and mapping using Rao-blackwellized particle filter with neural network for mini robots / Norhidayah Mohamad Yatim Mohamad Yatim, Norhidayah Neural networks (Computer science) Mini robots can be used in many applications such as in domestic, industrial or humanitarian fields. Typically, mini robot platforms are equipped with sparse and noisy sensors on board such as array of infrared sensors. In robotics, the ability to map the surrounding area and determine self-location is essential for a robot to be truly autonomous. This research aims to develop such capability known as Simultaneous Localization and Mapping (SLAM) algorithm for mini robots with array of infrared (IR) sensors. Existing methods had implemented either feature-based or occupancy grid map (OG) as map representation. In SLAM with feature-based map, prior knowledge of the environment is required to associate sensor measurements with the right features. OG map representation does not need for landmark identification but described occupancy of an area. In this research, to enable mini robots to operate in various environment, OG map with SLAM or grid-based SLAM algorithm was developed. Previous works in this domain had to assume for all walls in the environment are either parallel or perpendicular to each other. 2018 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/82558/1/82558.pdf Grid-based simultaneous localization and mapping using Rao-blackwellized particle filter with neural network for mini robots / Norhidayah Mohamad Yatim. (2018) PhD thesis, thesis, Universiti Teknologi MARA (UiTM). <http://terminalib.uitm.edu.my/82558.pdf> |
institution |
Universiti Teknologi Mara |
building |
Tun Abdul Razak Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Mara |
content_source |
UiTM Institutional Repository |
url_provider |
http://ir.uitm.edu.my/ |
language |
English |
topic |
Neural networks (Computer science) |
spellingShingle |
Neural networks (Computer science) Mohamad Yatim, Norhidayah Grid-based simultaneous localization and mapping using Rao-blackwellized particle filter with neural network for mini robots / Norhidayah Mohamad Yatim |
description |
Mini robots can be used in many applications such as in domestic, industrial or humanitarian fields. Typically, mini robot platforms are equipped with sparse and noisy sensors on board such as array of infrared sensors. In robotics, the ability to map the surrounding area and determine self-location is essential for a robot to be truly autonomous. This research aims to develop such capability known as Simultaneous Localization and Mapping (SLAM) algorithm for mini robots with array of infrared (IR) sensors. Existing methods had implemented either feature-based or occupancy grid map (OG) as map representation. In SLAM with feature-based map, prior knowledge of the environment is required to associate sensor measurements with the right features. OG map representation does not need for landmark identification but described occupancy of an area. In this research, to enable mini robots to operate in various environment, OG map with SLAM or grid-based SLAM algorithm was developed. Previous works in this domain had to assume for all walls in the environment are either parallel or perpendicular to each other. |
format |
Thesis |
author |
Mohamad Yatim, Norhidayah |
author_facet |
Mohamad Yatim, Norhidayah |
author_sort |
Mohamad Yatim, Norhidayah |
title |
Grid-based simultaneous localization and mapping using Rao-blackwellized particle filter with neural network for mini robots / Norhidayah Mohamad Yatim |
title_short |
Grid-based simultaneous localization and mapping using Rao-blackwellized particle filter with neural network for mini robots / Norhidayah Mohamad Yatim |
title_full |
Grid-based simultaneous localization and mapping using Rao-blackwellized particle filter with neural network for mini robots / Norhidayah Mohamad Yatim |
title_fullStr |
Grid-based simultaneous localization and mapping using Rao-blackwellized particle filter with neural network for mini robots / Norhidayah Mohamad Yatim |
title_full_unstemmed |
Grid-based simultaneous localization and mapping using Rao-blackwellized particle filter with neural network for mini robots / Norhidayah Mohamad Yatim |
title_sort |
grid-based simultaneous localization and mapping using rao-blackwellized particle filter with neural network for mini robots / norhidayah mohamad yatim |
publishDate |
2018 |
url |
https://ir.uitm.edu.my/id/eprint/82558/1/82558.pdf https://ir.uitm.edu.my/id/eprint/82558/ |
_version_ |
1793161833513746432 |
score |
13.18916 |