Computer vision for fruit harvesting robots - State of the art and challenges ahead

Keren Kapach, Ehud Barnea, Rotem Mairon, Yael Edan, Ohad Ben-Shahar

Research output: Contribution to journalArticlepeer-review

191 Scopus citations

Abstract

Despite extensive research conducted in machine vision for harvesting robots, practical success in this field of agrobotics is still limited. This article presents a comprehensive review of classical and state-of-the-art machine vision solutions employed in such systems, with special emphasis on the visual cues and machine vision algorithms used. We discuss the advantages and limitations of each approach and we examine these capacities in light of the challenges ahead. We conclude with suggested directions from the general computer vision literature which could assist our research community meet these challenges and bring us closer to the goal of practical selective fruit harvesting robots.

Original languageEnglish
Pages (from-to)4-34
Number of pages31
JournalInternational Journal of Computational Vision and Robotics
Volume3
Issue number1-2
DOIs
StatePublished - 1 Jan 2012

Keywords

  • Agricultural computer vision
  • Agrobotics
  • Agrovision
  • Fruit harvesting robots

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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