Sensors and systems for fruit detection and localization: A review

• We reviewed successes and challenges of sensing systems for fruit detection.
• We also reviewed the capabilities of sensors used for fruit localization.
• Challenges included occlusion, clustering and variable lighting condition.
• We presented future direction including amendment of orchard environment.
• Sensor fusion and human machine collaboration can also be areas for research.

This paper reviews the research and development of machine vision systems for fruit detection and localization for robotic harvesting and/or crop-load estimation of specialty tree crops including apples, pears, and citrus. Variable lighting condition, occlusions, and clustering are some of the important issues needed to be addressed for accurate detection and localization of fruit in orchard environment. To address these issues, various techniques have been investigated using different types of sensors and their combinations as well as with different image processing techniques. This paper summarizes various techniques and their advantages and disadvantages in detecting fruit in plant or tree canopies. The paper also summarizes the sensors and systems developed and used by researchers to localize fruit as well as the potential and limitations of those systems. Finally, major challenges for the successful application of machine vision system for robotic fruit harvesting and crop-load estimation, and potential future directions for research and development are discussed.