Image-based mapping system for transplanted seedlings

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Show simple item record McGahee, Kyle 2016-11-18T15:46:12Z 2016-11-18T15:46:12Z 2016-12-01 en_US
dc.description.abstract Developments in farm related technology have increased the importance of mapping individual plants in the field. An automated mapping system allows the size of these fields to scale up without being hindered by time-intensive, manual surveying. This research focuses on the development of a mapping system which uses geo-located images of the field to automatically locate plants and determine their coordinates. Additionally, this mapping process is capable of differentiating between groupings of plants by using Quick Response (QR) codes. This research applies to green plants that have been grown into seedlings before being planted, known as transplants, and for fields that are planted in nominally straight rows. The development of this mapping system is presented in two stages. First is the design of a robotic platform equipped with a Real Time Kinematic (RTK) receiver that is capable of traversing the field to capture images. Second is the post-processing pipeline which converts the images into a field map. This mapping system was applied to a field at the Land Institute containing approximately 25,000 transplants. The results show the mapped plant locations are accurate to within a few inches, and the use of QR codes is effective for identifying plant groups. These results demonstrate this system is successful in mapping large fields. However, the high overall complexity makes the system restrictive for smaller fields where a simpler solution may be preferable. en_US
dc.description.sponsorship National Science Foundation en_US
dc.language.iso en_US en_US
dc.publisher Kansas State University en
dc.subject Mapping en_US
dc.subject Plant identification en_US
dc.subject Robot en_US
dc.subject Coordinates en_US
dc.title Image-based mapping system for transplanted seedlings en_US
dc.type Thesis en_US Master of Science en_US
dc.description.level Masters en_US
dc.description.department Department of Mechanical and Nuclear Engineering en_US
dc.description.advisor Dale Schinstock en_US 2016 en_US December en_US

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