Harvesting Robots for High‐value Crops: State‐of‐the‐art Review and Challenges Ahead

By Cornelis Wouter Bac, Eldert J. van Henten, Jochen Hemming, Yael Edan. J. Field Robotics, 2014

615 citations recorded by the source corpus.

Subfields: Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/7338edc0af83cf864fbe7d75abb2dc6a08995747

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In Plant Science

Citations in the corpus

Advances in Agriculture Robotics: A State-of-the-Art Review and Challenges Ahead (2021, positive): “In this sense, there are review works that address the use of robots in agriculture to perform general tasks, as in [15–17], or to improve the performance of specific tasks, such as harvesting high-value crops [18] and solving wheeled mobile robots’ navigation problems [19].”
Robotic kiwifruit harvesting using machine vision, convolutional neural networks, and robotic arms (2019, background): “Research toward overcoming these problems is gaining in popularity as de55 mand for agricultural automation increases globally [2, 3, 4, 5, 6].”
Research and development in agricultural robotics: a perspective of digital farming. (2018, background): “…various research groups to address these challenges, however there is currently no report of a commercial robotic harvesting for fresh fruit market [169] , mainly due to the extremely variable heterogeneous working condition and the complex and unpredicted tasks involved with different fruit and…”
DeepFruits: A Fruit Detection System Using Deep Neural Networks (2016, background): “For these reasons, there has been growing interest in the use of agricultural robots for harvesting fruit and vegetables over the past three decades [2,3].”
Automation in Agriculture by Machine and Deep Learning Techniques: A Review of Recent Developments (2021, background): “Some interesting future recommendations including modification in the environment of crops, innovative robotic designs, and other important factors like safety and economy were also summarized (Bac et al., 2014).”
Recognition and Localization Methods for Vision-Based Fruit Picking Robots: A Review (2020, background): “In fruit recognition, researchers applied deep learning convolutional neural networks (CNN) to the visual techniques of agricultural robots (Yang et al., 2016; Bargoti and Underwood, 2017; Chen et al., 2017; Rahnemoonfar and Sheppard, 2017; Tahir and Badshah, 2018).”
Agricultural Robotics: The Future of Robotic Agriculture (2018, background): “er assist in choosing the right time to harvest the crop • Selective Harvesting: Selective harvesting involves harvesting only those parts of the crop that meet certain quality or quantity thresholds [57]. Two criteria are needed: the ability to sense the required quality factor before harvest (in-f”