Active Perception Fruit Harvesting Robots - A Systematic Review

• Type: Another Publication in an International Scientific Journal
• Date: 2022

Authors

Magalhaes, SA (Author) Other; António Paulo Moreira (Author) FEUP; Filipe Neves Santos (Author) FEUP; Dias, J (Author) Other

Journal

Title: Journal of Intelligent and Robotic Systems: Theory and Applications

Vol. 105

Final page: 14

ISSN: 0921-0296

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 0 Citations

Scopus

Other information

Authenticus ID: P-00W-HV9

DOI: 10.1007/s10846-022-01595-3

Abstract (EN): This paper studies the state-of-the-art of active perception solutions for manipulation in agriculture and suggests a possible architecture for an active perception system for harvesting in agriculture. Research and developing robots for agricultural context is a challenge, particularly for harvesting and pruning context applications. These applications normally consider mobile manipulators and their cognitive part has many challenges. Active perception systems look reasonable approach for fruit assessment robustly and economically. This systematic literature review focus in the topic of active perception for fruits harvesting robots. The search was performed in five different databases. The search resumed into 1034 publications from which only 195 publications where considered for inclusion in this review after analysis. We conclude that the most of researches are mainly about fruit detection and segmentation in two-dimensional space using evenly classic computer vision strategies and deep learning models. For harvesting, multiple viewpoint and visual servoing are the most commonly used strategies. The research of these last topics does not look robust yet, and require further analysis and improvements for better results on fruit harvesting.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 22