Cucumber picking robots: Technological progress, challenges, and future directions

Read full text
Authors: Arshed Ahmed, Zhao Zhang, Shahram Hamza Manzoor, Mahmoud A. Abdelhamid, Noor Gul, Rashed Ahmed, Mustafa Mhamed, Ruixuan Sun, Cunming Hao, Weihao Huo, Yingkun Zhang, Neili Machado Garcia
Cited by: 6
References: 52

Abstract

Cucumber is a popular fruit, and its harvest is labor-intensive. Increasing labor costs and a shrinking labor pool have motivated the development of robotic picking. This article conducts a comprehensive study of cucumber picking robots (CPRs) in greenhouses, evaluating technological advancements and future trends. The unique morphology of cucumbers, which differs from other fruits, requires a specialized end-effector to handle their elongated shape and delicate skin without causing injury. Despite rapid progress in agricultural robotics, inefficiency in robust cucumber recognition, especially when leaves have the same color, has restricted the large-scale deployment of picking robots. Recent breakthroughs in vision-based control, optimized vision acquisition, improved cucumber recognition algorithms, and effective eye-hand coordination offer promising solutions to these limitations. This study provides a detailed overview of five research areas related to CPRs: historical evolution, vision control guiding, detection mechanisms and identification, cucumber-adaptive end effectors, and motion paths. It also discusses the challenges involved in implementing these techniques. The review offers a concise overview that benefits stakeholders and accelerates the development of commercially viable CPRs.

Fields of Study & Subjects

Smart Agriculture and AI Tree Root and Stability Studies Plant Disease Management Techniques

Publication details

Journal / source
Smart Agricultural Technology
Publisher
Elsevier BV
Volume
13
Pages
101813–101813
Publication date
19 January 2026
Language
EN