RA-L 201861 citations

Efficacy of Mechanical Weeding Tools: A Study Into Alternative Weed Management Strategies Enabled by Robotics

Chris McCool, James Beattie, Jennifer Firn, Christopher F. Lehnert, Jason Kulk, Owen Bawden, Ray Russell, Tristan Perez

Abstract

The rise of herbicide resistant weed species has reinvigorated research in nonchemical methods for weed management. Robots, such as AgBot II, that can detect and classify weeds as they traverse a field are a key enabling factor for individualised treatment of weed species. Integral to the invidualized treatment of weed species are the the nonherbicide methods through which the weeds are managed. This letter explores mechanical methods as an alternative to weed management. Three implements are considered: below-surface tilling (arrow hoe), above-surface tilling (tines), and a cutting mechanism. These mechanisms were evaluated in a controlled field with varying rates of application to herbicide-resistant weeds of interest for Queensland, Australia. Statistical analysis demonstrated the efficacy of these implements and highlighted the importance of early intervention. It was found that a tine, deployed automatically on AgBot II, was effective for all of the weeds considered in this study, leading to an overall survival probability of 0.28 ± 0.15. Further analysis demonstrated the significance of treatment time with late intervention commencing at week 6 resulting in a survival probability of 0.54 ± 0.08 vs 0.24 ± 0.18 for earlier intervention at week 4.

BibTeX
@inproceedings{ral2018_efficacyofmechan,
  title = {Efficacy of Mechanical Weeding Tools: A Study Into Alternative Weed Management Strategies Enabled by Robotics},
  author = {Chris McCool and James Beattie and Jennifer Firn and Christopher F. Lehnert and Jason Kulk and Owen Bawden and Ray Russell and Tristan Perez},
  booktitle = {RA-L 2018},
  year = {2018}
}
Efficacy of Mechanical Weeding Tools: A Study Into Alternative Weed Management Strategies Enabled by Robotics · RA-L 2018