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.
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Claims 0
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