Position estimation of autonomous guided vehicle

This thesis presents the development and application of a sensor fusion algorithm in positioning. The theoretical background behind the algorithm is based on the extended Kalman filter. By merging information from different sensors such as the Differential Global Positioning System (DGPS), rate g...

Full description

Saved in:
Bibliographic Details
Main Author: Goh, Ching Tard.
Other Authors: Wang, Han
Format: Theses and Dissertations
Published: 2008
Subjects:
Online Access:http://hdl.handle.net/10356/4296
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
id sg-ntu-dr.10356-4296
record_format dspace
spelling sg-ntu-dr.10356-42962023-07-04T15:58:25Z Position estimation of autonomous guided vehicle Goh, Ching Tard. Wang, Han School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics This thesis presents the development and application of a sensor fusion algorithm in positioning. The theoretical background behind the algorithm is based on the extended Kalman filter. By merging information from different sensors such as the Differential Global Positioning System (DGPS), rate gyroscope and odometers, the filter is able to predict optimally the position and orientation of a 2-wheel steerable vehicle. In the filter, an enhanced kinematic process or vehicle model that accounts for the side slips experienced at the vehicle wheels is employed. These slip parameters that conform to the angles between the actual translated and pointed directions of the vehicle tires can affect the accuracy and consistency of the estimation system. Comparison between the enhanced model and another (without the slip consideration and based on pure kinematics) indicates improvements in the estimations as well as the orientation rate innovations with the slip compensation. Master of Engineering 2008-09-17T09:48:47Z 2008-09-17T09:48:47Z 1999 1999 Thesis http://hdl.handle.net/10356/4296 Nanyang Technological University application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
topic DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics
Goh, Ching Tard.
Position estimation of autonomous guided vehicle
description This thesis presents the development and application of a sensor fusion algorithm in positioning. The theoretical background behind the algorithm is based on the extended Kalman filter. By merging information from different sensors such as the Differential Global Positioning System (DGPS), rate gyroscope and odometers, the filter is able to predict optimally the position and orientation of a 2-wheel steerable vehicle. In the filter, an enhanced kinematic process or vehicle model that accounts for the side slips experienced at the vehicle wheels is employed. These slip parameters that conform to the angles between the actual translated and pointed directions of the vehicle tires can affect the accuracy and consistency of the estimation system. Comparison between the enhanced model and another (without the slip consideration and based on pure kinematics) indicates improvements in the estimations as well as the orientation rate innovations with the slip compensation.
author2 Wang, Han
author_facet Wang, Han
Goh, Ching Tard.
format Theses and Dissertations
author Goh, Ching Tard.
author_sort Goh, Ching Tard.
title Position estimation of autonomous guided vehicle
title_short Position estimation of autonomous guided vehicle
title_full Position estimation of autonomous guided vehicle
title_fullStr Position estimation of autonomous guided vehicle
title_full_unstemmed Position estimation of autonomous guided vehicle
title_sort position estimation of autonomous guided vehicle
publishDate 2008
url http://hdl.handle.net/10356/4296
_version_ 1772827465728655360