Computer vision for fruit harvesting robots – state of the art and challenges ahead

  • Authors:

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

  • Affiliations:

  • Department of Industrial Engineering and Management, Ben-Gurion University, P.O. Box 653, Beer-Sheva, 84105, Israel.;Computer Science Department, Ben-Gurion University, P.O. Box 653, Beer-Sheva, 84105, Israel.;Computer Science Department, Ben-Gurion University, P.O. Box 653, Beer-Sheva, 84105, Israel.;Department of Industrial Engineering and Management, Ben-Gurion University, P.O. Box 653, Beer-Sheva, 84105, Israel.;Computer Science Department, Ben-Gurion University, P.O. Box 653, Beer-Sheva, 84105, Israel

  • Venue:
  • International Journal of Computational Vision and Robotics
  • Year:
  • 2012

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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.