Vision based guidance of an agricultural combine

A machine vision based guidance system for agricultural combines was developed at the University of Illinois. Three machine vision guidance algorithms were developed and evaluated for guidance. The first algorithm, the Low Head Mounted Camera Algorithm (LHMCA), utilized images from a head mounted camera that directly viewed the cut/uncut crop edge. The LHMCA was used under actual field conditions in 1999; however, shadows and poor crop condition compromised performance of the algorithm. The High Head Mounted Camera Algorithm (HHMCA) used a camera mounted on the head directly above the cut/uncut edge to image the scene. The HHMCA performed well in the laboratory; poor image quality in the field restricted the use of the algorithm. The Cab Mounted Camera Algorithm (CMCA) processed images from a monochrome image sensor mounted above the cab of the combine. The CMCA closely mimics methodology used by the operator. The CMCA was used to automatically harvest 4.6 ha (12.0 a) of corn during both daylight and at night. The resulting accuracy of the guidance system (13.3 cm) was not statistically different from the accuracy of the GPS position recording system (11.0 cm).

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Agricultural Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Benson, Eric Randolph

Contributors dc:contributor

• Reid, John F.

• Engineering, Mechanical

Language dc:language

eng

Identifier

(MiAaPQ)AAI3017023

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/86042