Development of visual navigation system for AGV in complex environment
The usage of autonomously guided vehicles has enabled factories and warehouses to improve on their usage of manpower and logistics. At present, AGVs found in the industry has widely exploited the use of line tracking and magnetic strips to help guide their maneuvers. This technology has since mature...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2020
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| Online Access: | https://hdl.handle.net/10356/140806 |
| _version_ | 1826110870902538240 |
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| author | Kang, Nicholas Jay Hung |
| author2 | Xie Lihua |
| author_facet | Xie Lihua Kang, Nicholas Jay Hung |
| author_sort | Kang, Nicholas Jay Hung |
| collection | NTU |
| description | The usage of autonomously guided vehicles has enabled factories and warehouses to improve on their usage of manpower and logistics. At present, AGVs found in the industry has widely exploited the use of line tracking and magnetic strips to help guide their maneuvers. This technology has since matured, regarding it as a normality in the field. It is only in recent years has engineers dabbled with other means such as vision-based navigation. Popularity of this technology stamps from the decrease in cost of these cameras used in the vehicles. These compact, robust image processors act as eyes for the AGV enabling it to see the world in a different light. Still being considered a novel platform, there is much to be explored and perfect. Challenges posed to image guidance would include an ever-changing environment with the system reluctance to respond to any quick changes in obstacles. There also poses the problem of calibration when the light entering the camera at any given moment may vary from the recognized hue and saturation. Technologies that fall in correlation to image guidance will also include blind mapping to assist in the vehicle’s understanding of its environment. Logical reasoning directive for the deciphering methods to handle obstacles should it encounter one. Intuitive calibration for camera to allow the vehicle comprehensive means to calibrate color calibration on the go. The area in which the report will focus on is improving on the current existing SLAM methods which AGVs use to localize and eventually navigate itself in. |
| first_indexed | 2024-10-01T02:41:16Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/140806 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:41:16Z |
| publishDate | 2020 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1408062023-07-07T18:53:47Z Development of visual navigation system for AGV in complex environment Kang, Nicholas Jay Hung Xie Lihua School of Electrical and Electronic Engineering elhxie@ntu.edu.sg Engineering::Electrical and electronic engineering The usage of autonomously guided vehicles has enabled factories and warehouses to improve on their usage of manpower and logistics. At present, AGVs found in the industry has widely exploited the use of line tracking and magnetic strips to help guide their maneuvers. This technology has since matured, regarding it as a normality in the field. It is only in recent years has engineers dabbled with other means such as vision-based navigation. Popularity of this technology stamps from the decrease in cost of these cameras used in the vehicles. These compact, robust image processors act as eyes for the AGV enabling it to see the world in a different light. Still being considered a novel platform, there is much to be explored and perfect. Challenges posed to image guidance would include an ever-changing environment with the system reluctance to respond to any quick changes in obstacles. There also poses the problem of calibration when the light entering the camera at any given moment may vary from the recognized hue and saturation. Technologies that fall in correlation to image guidance will also include blind mapping to assist in the vehicle’s understanding of its environment. Logical reasoning directive for the deciphering methods to handle obstacles should it encounter one. Intuitive calibration for camera to allow the vehicle comprehensive means to calibrate color calibration on the go. The area in which the report will focus on is improving on the current existing SLAM methods which AGVs use to localize and eventually navigate itself in. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-06-02T04:49:56Z 2020-06-02T04:49:56Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/140806 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Kang, Nicholas Jay Hung Development of visual navigation system for AGV in complex environment |
| title | Development of visual navigation system for AGV in complex environment |
| title_full | Development of visual navigation system for AGV in complex environment |
| title_fullStr | Development of visual navigation system for AGV in complex environment |
| title_full_unstemmed | Development of visual navigation system for AGV in complex environment |
| title_short | Development of visual navigation system for AGV in complex environment |
| title_sort | development of visual navigation system for agv in complex environment |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/140806 |
| work_keys_str_mv | AT kangnicholasjayhung developmentofvisualnavigationsystemforagvincomplexenvironment |