Active Perception Fruit Harvesting Robots - A Systematic Review

• Tipo: Outra Publicação em Revista Científica Internacional
• Data: 2022

Autores

Magalhaes, SA (Autor) Outra; António Paulo Moreira (Autor) FEUP; Filipe Neves Santos (Autor) FEUP; Dias, J (Autor) Outra

Revista

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

Vol. 105

Página Final: 14

ISSN: 0921-0296

Editora: Springer Nature

Indexação

ISI Web of Knowledge - 0 Citações

Scopus

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 22