AGV precision docking in smart factory

Automated guided vehicle (AGV) has become a research hotspot in recent years because of its great performance in executing repetitive tasks. The main concerns of the current methodology are to maintain the high precision of AGV docking after being maneuvered to multiple goals and to minimize human i...

Full description

Saved in:
Bibliographic Details
Main Author: Tan, Jia Yi
Other Authors: Xie Lihua
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/149223
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-149223
record_format dspace
spelling sg-ntu-dr.10356-1492232023-07-07T18:17:55Z AGV precision docking in smart factory Tan, Jia Yi Xie Lihua School of Electrical and Electronic Engineering Delta-NTU Corporate Laboratory ELHXIE@ntu.edu.sg Engineering::Electrical and electronic engineering Automated guided vehicle (AGV) has become a research hotspot in recent years because of its great performance in executing repetitive tasks. The main concerns of the current methodology are to maintain the high precision of AGV docking after being maneuvered to multiple goals and to minimize human intervention in the process of docking. Therefore, this project proposes the implementation of Ultra Wideband (UWB) coordinating system to supplement the vision-based docking mechanism using LiDAR sensor alone. In recent studies, UWB sensor is becoming more popular because it is able to provide precise localization and cover a larger operating area as compared to other wireless positioning technologies. Therefore, a UWB based navigation algorithm is developed in this project using the concept of Potential Field Method to perform tag following, collision avoidance and path tracking tasks. This algorithm can navigate the AGV to the goal with maximum linear error of 40 centimeters and maximum angular error of 12 degrees. Other than the navigation algorithm, UWB sensors are also used to perform automated map scanning and provide the initial pose estimate for the adaptive Monte Carlo localization (AMCL) so that the AGV can be successfully initialized at any position in the map. After the localization process, a ROS package “move_base” is used to perform AGV precision docking to single station and multiple stations. Eventually, the AGV can be docked to both the dynamic station and static station with comparable accuracy around 25 centimeters and to multiple linearly oriented stations with deviation lower than 15 centimeters. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-05-28T07:38:06Z 2021-05-28T07:38:06Z 2021 Final Year Project (FYP) Tan, J. Y. (2021). AGV precision docking in smart factory. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149223 https://hdl.handle.net/10356/149223 en A1190-201 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Tan, Jia Yi
AGV precision docking in smart factory
description Automated guided vehicle (AGV) has become a research hotspot in recent years because of its great performance in executing repetitive tasks. The main concerns of the current methodology are to maintain the high precision of AGV docking after being maneuvered to multiple goals and to minimize human intervention in the process of docking. Therefore, this project proposes the implementation of Ultra Wideband (UWB) coordinating system to supplement the vision-based docking mechanism using LiDAR sensor alone. In recent studies, UWB sensor is becoming more popular because it is able to provide precise localization and cover a larger operating area as compared to other wireless positioning technologies. Therefore, a UWB based navigation algorithm is developed in this project using the concept of Potential Field Method to perform tag following, collision avoidance and path tracking tasks. This algorithm can navigate the AGV to the goal with maximum linear error of 40 centimeters and maximum angular error of 12 degrees. Other than the navigation algorithm, UWB sensors are also used to perform automated map scanning and provide the initial pose estimate for the adaptive Monte Carlo localization (AMCL) so that the AGV can be successfully initialized at any position in the map. After the localization process, a ROS package “move_base” is used to perform AGV precision docking to single station and multiple stations. Eventually, the AGV can be docked to both the dynamic station and static station with comparable accuracy around 25 centimeters and to multiple linearly oriented stations with deviation lower than 15 centimeters.
author2 Xie Lihua
author_facet Xie Lihua
Tan, Jia Yi
format Final Year Project
author Tan, Jia Yi
author_sort Tan, Jia Yi
title AGV precision docking in smart factory
title_short AGV precision docking in smart factory
title_full AGV precision docking in smart factory
title_fullStr AGV precision docking in smart factory
title_full_unstemmed AGV precision docking in smart factory
title_sort agv precision docking in smart factory
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/149223
_version_ 1772825606164054016