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Carnegie Mellon Robotics Institute

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Abstract

Automation of agricultural harvesting equipment in the near term appears both economically viable and technically feasible. This paper describes a vision-based algorithm which guides a harvester by tracking the line between cut and uncut crop. Using this algorithm, a harvester has successfully cut roughly one acre of crop to date, at speeds of up to 4.5 miles an hour in an actual alfalfa field. A broad range of methods for detecting the crop cut boundary were considered, including both range-based and vision-based techniques; several of these methods were implemented and evaluated on data from an alfalfa field. The final crop-line detection algorithm is presented, which operates by computing the best-fit step function of a normalized-color measure of each row of an RGB image. Results of the algorithm on some sample crop images are shown, and potential improvements are discussed.

Notes

Associated Center(s) / Consortia: National Robotics Engineering Center

Associated Project(s): Demeter and Row Crop Harvesting

Text Reference

Mark Ollis and Anthony (Tony) Stentz, "First Results in Vision-Based Crop Line Tracking," Proceedings of the IEEE International Conference on Robotics and Automation, April, 1996, pp. 951 - 956.

BibTeX Reference

@inproceedings{Ollis_1996_1211,
   author = "Mark Ollis and Anthony (Tony) Stentz",
   title = "First Results in Vision-Based Crop Line Tracking",
   booktitle = "Proceedings of the IEEE International Conference on Robotics and Automation",
   pages = "951 - 956",
   month = "April",
   year = "1996",
   volume = "1",
}

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