Authors: Travis Esau, Craig MacEachern, Aitazaz Farooque, Qamar Zaman
Identifier: CSBE21456
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Published in: CSBE-SCGAB Technical Conferences » 5th CIGR and AGM Quebec City 2021 » Regular Sessions

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Description: As part of the progression towards a fully automated wild blueberry harvester, GNSS autosteer was assessed for its ability to accurately steer the harvester. This study analyzed John Deere?s Autotrac 300, with SF1 and SF3 correction signals on the Starfire 6000 receiver for their ability to maintain consistent pass-to-pass accuracy. Autosteer has seen limited success for harvesting wild blueberries due to the low travel speeds and rough terrain encountered in most fields. Harvesting speeds of 0.31 m s-1, 0.45 m s-1 and 0.58 m s-1 were assessed, and it was determined that there were no significant differences in pass-to-pass accuracy among any of the speeds (p = 0.174). Comparison of the correction signals demonstrated that SF3 with a mean absolute pass-to-pass discrepancy of 73.8 ? 7.2 mm was a significant improvement on SF1 which, had a mean absolute pass-to-pass discrepancy of 98.4 ? 7.2 mm (p < 0.001). Both signals were a significant improvement on manual steering by skilled operators which yielded a mean absolute pass-to-pass discrepancy of 113.2 ? 10.1 mm (p < 0.001). None of the signals were able to achieve the accuracy levels advertised by the manufacturer though, this is likely due to the unique constraints of the wild blueberry harvesting system and the inability to ensure ideal satellite conditions. Nevertheless, the results of this study lay promising groundwork for full automation of the wild blueberry harvester by demonstrating that GNSS autosteer systems can perform better than skilled operators.

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Date: 2021-06-11
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Conference name: 5th CIGR International Conference and CSBE-SCGAB AGM 2021, Quebec City,QC, 11-14 May 2021.
Session name: Machinery and Robotic Systems 3

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Type: Text.Abstract
Publication type: Presentation
Coverage: Canada
Language 1: en
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Rights: Canadian Society for Bioengineering
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