Current Research Status and Development Trends of Key Technologies for Pear Harvesting Robots Article Swipe
Hongtu Zhang
,
Binbin Wang
,
Liyang Su
,
Ziyue Yu
,
Xinchao Liu
,
Xianglong Meng
,
Kaijun Zhao
,
Xiongkui He
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/agronomy15092163
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/agronomy15092163
In response to the global labor shortage in the pear industry, the use of robots for harvesting has become an inevitable trend. Developing pear harvesting robots for orchard operations is of significant importance. This paper systematically reviews the progress of three key technologies in pear harvesting robotics: Firstly, in the field of recognition technology, traditional methods are limited by sensitivity to lighting conditions and occlusion errors. In contrast, deep learning models, such as the optimized YOLO series and two-stage architectures, significantly enhance robustness in complex scenes and improve handling of overlapping fruits. Secondly, positioning technology has advanced from 2D pixel coordinate acquisition to 3D spatial reconstruction, with the integration of posture estimation (binocular vision + IMU) addressing occlusion issues. Finally, the end effector is categorized based on harvesting mechanisms: gripping–twisting, shearing, and adsorption (vacuum negative pressure). However, challenges such as fruit skin damage and positioning bottlenecks remain. The current technologies still face three major challenges: low harvesting efficiency, high fruit damage rates, and high equipment costs. In the future, breakthroughs are expected through the integration of agricultural machinery and agronomy (standardized planting), multi-arm collaborative operation, lightweight algorithms, and 5G cloud computing.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/agronomy15092163
- https://www.mdpi.com/2073-4395/15/9/2163/pdf?version=1757499202
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All OpenAlex metadata
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Current Research Status and Development Trends of Key Technologies for Pear Harvesting RobotsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-09-10Full publication date if available
- Authors
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Hongtu Zhang, Binbin Wang, Liyang Su, Ziyue Yu, Xinchao Liu, Xianglong Meng, Kaijun Zhao, Xiongkui HeList of authors in order
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https://doi.org/10.3390/agronomy15092163Publisher landing page
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https://www.mdpi.com/2073-4395/15/9/2163/pdf?version=1757499202Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2073-4395/15/9/2163/pdf?version=1757499202Direct OA link when available
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.has | 17, 95 |
| abstract_inverted_index.key | 41 |
| abstract_inverted_index.low | 155 |
| abstract_inverted_index.the | 3, 8, 11, 37, 49, 73, 107, 120, 167, 173 |
| abstract_inverted_index.use | 12 |
| abstract_inverted_index.IMU) | 115 |
| abstract_inverted_index.This | 33 |
| abstract_inverted_index.YOLO | 75 |
| abstract_inverted_index.deep | 68 |
| abstract_inverted_index.face | 151 |
| abstract_inverted_index.from | 97 |
| abstract_inverted_index.high | 158, 163 |
| abstract_inverted_index.pear | 9, 23, 44 |
| abstract_inverted_index.skin | 141 |
| abstract_inverted_index.such | 71, 138 |
| abstract_inverted_index.with | 106 |
| abstract_inverted_index.based | 125 |
| abstract_inverted_index.cloud | 189 |
| abstract_inverted_index.field | 50 |
| abstract_inverted_index.fruit | 140, 159 |
| abstract_inverted_index.labor | 5 |
| abstract_inverted_index.major | 153 |
| abstract_inverted_index.paper | 34 |
| abstract_inverted_index.pixel | 99 |
| abstract_inverted_index.still | 150 |
| abstract_inverted_index.three | 40, 152 |
| abstract_inverted_index.become | 18 |
| abstract_inverted_index.costs. | 165 |
| abstract_inverted_index.damage | 142, 160 |
| abstract_inverted_index.global | 4 |
| abstract_inverted_index.rates, | 161 |
| abstract_inverted_index.robots | 14, 25 |
| abstract_inverted_index.scenes | 85 |
| abstract_inverted_index.series | 76 |
| abstract_inverted_index.trend. | 21 |
| abstract_inverted_index.vision | 113 |
| abstract_inverted_index.(vacuum | 133 |
| abstract_inverted_index.complex | 84 |
| abstract_inverted_index.current | 148 |
| abstract_inverted_index.enhance | 81 |
| abstract_inverted_index.errors. | 65 |
| abstract_inverted_index.fruits. | 91 |
| abstract_inverted_index.future, | 168 |
| abstract_inverted_index.improve | 87 |
| abstract_inverted_index.issues. | 118 |
| abstract_inverted_index.limited | 57 |
| abstract_inverted_index.methods | 55 |
| abstract_inverted_index.models, | 70 |
| abstract_inverted_index.orchard | 27 |
| abstract_inverted_index.posture | 110 |
| abstract_inverted_index.remain. | 146 |
| abstract_inverted_index.reviews | 36 |
| abstract_inverted_index.spatial | 104 |
| abstract_inverted_index.through | 172 |
| abstract_inverted_index.Finally, | 119 |
| abstract_inverted_index.Firstly, | 47 |
| abstract_inverted_index.However, | 136 |
| abstract_inverted_index.advanced | 96 |
| abstract_inverted_index.agronomy | 179 |
| abstract_inverted_index.effector | 122 |
| abstract_inverted_index.expected | 171 |
| abstract_inverted_index.handling | 88 |
| abstract_inverted_index.learning | 69 |
| abstract_inverted_index.lighting | 61 |
| abstract_inverted_index.negative | 134 |
| abstract_inverted_index.progress | 38 |
| abstract_inverted_index.response | 1 |
| abstract_inverted_index.shortage | 6 |
| abstract_inverted_index.Secondly, | 92 |
| abstract_inverted_index.contrast, | 67 |
| abstract_inverted_index.equipment | 164 |
| abstract_inverted_index.industry, | 10 |
| abstract_inverted_index.machinery | 177 |
| abstract_inverted_index.multi-arm | 182 |
| abstract_inverted_index.occlusion | 64, 117 |
| abstract_inverted_index.optimized | 74 |
| abstract_inverted_index.robotics: | 46 |
| abstract_inverted_index.shearing, | 130 |
| abstract_inverted_index.two-stage | 78 |
| abstract_inverted_index.(binocular | 112 |
| abstract_inverted_index.Developing | 22 |
| abstract_inverted_index.addressing | 116 |
| abstract_inverted_index.adsorption | 132 |
| abstract_inverted_index.challenges | 137 |
| abstract_inverted_index.computing. | 190 |
| abstract_inverted_index.conditions | 62 |
| abstract_inverted_index.coordinate | 100 |
| abstract_inverted_index.estimation | 111 |
| abstract_inverted_index.harvesting | 16, 24, 45, 127, 156 |
| abstract_inverted_index.inevitable | 20 |
| abstract_inverted_index.operation, | 184 |
| abstract_inverted_index.operations | 28 |
| abstract_inverted_index.planting), | 181 |
| abstract_inverted_index.pressure). | 135 |
| abstract_inverted_index.robustness | 82 |
| abstract_inverted_index.technology | 94 |
| abstract_inverted_index.acquisition | 101 |
| abstract_inverted_index.algorithms, | 186 |
| abstract_inverted_index.bottlenecks | 145 |
| abstract_inverted_index.categorized | 124 |
| abstract_inverted_index.challenges: | 154 |
| abstract_inverted_index.efficiency, | 157 |
| abstract_inverted_index.importance. | 32 |
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| abstract_inverted_index.lightweight | 185 |
| abstract_inverted_index.mechanisms: | 128 |
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| abstract_inverted_index.positioning | 93, 144 |
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| abstract_inverted_index.sensitivity | 59 |
| abstract_inverted_index.significant | 31 |
| abstract_inverted_index.technology, | 53 |
| abstract_inverted_index.traditional | 54 |
| abstract_inverted_index.agricultural | 176 |
| abstract_inverted_index.technologies | 42, 149 |
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| abstract_inverted_index.breakthroughs | 169 |
| abstract_inverted_index.collaborative | 183 |
| abstract_inverted_index.significantly | 80 |
| abstract_inverted_index.architectures, | 79 |
| abstract_inverted_index.systematically | 35 |
| abstract_inverted_index.reconstruction, | 105 |
| abstract_inverted_index.gripping–twisting, | 129 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5060893801 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 8 |
| corresponding_institution_ids | https://openalex.org/I52158045 |
| citation_normalized_percentile.value | 0.28331905 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |