Enhanced YOLOv5 with ECA Module for Vision-Based Apple Harvesting Using a 6-DOF Robotic Arm in Occluded Environments Article Swipe
Yan Xu
,
X. Qiao
,
Li Ding
,
Xinghao Li
,
Zhiyu Chen
,
Xiang Yue
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/agriculture15171850
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/agriculture15171850
Accurate target recognition and localization remain significant challenges for robotic fruit harvesting in unstructured orchard environments characterized by branch occlusion and leaf clutter. To address the difficulty in identifying and locating apples under such visually complex conditions, this paper proposes an improved YOLOv5-based visual recognition algorithm incorporating an efficient channel attention (ECA) module. The ECA module is strategically integrated into specific C3 layers (C3-3, C3-6, C3-9) of the YOLOv5 network architecture to enhance feature representation for occluded targets. During operation, the system simultaneously acquires apple pose information and achieves precise spatial localization through coordinate transformation matrices. Comprehensive experimental evaluations demonstrate the effectiveness of the proposed system. The custom-designed six-degree-of-freedom (6-DOF) robotic arm exhibits a wide operational range with a maximum working angle of 120°. The ECA-enhanced YOLOv5 model achieves a confidence level of 90% and an impressive in-range apple recognition rate of 98%, representing a 2.5% improvement in the mean Average Precision (mAP) compared to the baseline YOLOv5s algorithm. The end-effector positioning error is consistently controlled within 1.5 mm. The motion planning success rate reaches 92%, with the picking completed within 23 s per apple. This work provides a novel and effective vision recognition solution for future development of harvesting robots.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/agriculture15171850
- https://www.mdpi.com/2077-0472/15/17/1850/pdf?version=1756484386
- OA Status
- gold
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4413817320
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4413817320Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/agriculture15171850Digital Object Identifier
- Title
-
Enhanced YOLOv5 with ECA Module for Vision-Based Apple Harvesting Using a 6-DOF Robotic Arm in Occluded EnvironmentsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-08-29Full publication date if available
- Authors
-
Yan Xu, X. Qiao, Li Ding, Xinghao Li, Zhiyu Chen, Xiang YueList of authors in order
- Landing page
-
https://doi.org/10.3390/agriculture15171850Publisher landing page
- PDF URL
-
https://www.mdpi.com/2077-0472/15/17/1850/pdf?version=1756484386Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2077-0472/15/17/1850/pdf?version=1756484386Direct OA link when available
- Concepts
-
Robotic arm, Computer vision, Artificial intelligence, Computer science, Environmental science, Agricultural engineering, EngineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
23Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.work | 186 |
| abstract_inverted_index.(ECA) | 51 |
| abstract_inverted_index.(mAP) | 152 |
| abstract_inverted_index.C3-6, | 64 |
| abstract_inverted_index.C3-9) | 65 |
| abstract_inverted_index.angle | 121 |
| abstract_inverted_index.apple | 84, 138 |
| abstract_inverted_index.error | 162 |
| abstract_inverted_index.fruit | 10 |
| abstract_inverted_index.level | 131 |
| abstract_inverted_index.model | 127 |
| abstract_inverted_index.novel | 189 |
| abstract_inverted_index.paper | 38 |
| abstract_inverted_index.range | 116 |
| abstract_inverted_index.under | 32 |
| abstract_inverted_index.(C3-3, | 63 |
| abstract_inverted_index.120°. | 123 |
| abstract_inverted_index.During | 78 |
| abstract_inverted_index.YOLOv5 | 68, 126 |
| abstract_inverted_index.apple. | 184 |
| abstract_inverted_index.apples | 31 |
| abstract_inverted_index.branch | 18 |
| abstract_inverted_index.future | 196 |
| abstract_inverted_index.layers | 62 |
| abstract_inverted_index.module | 55 |
| abstract_inverted_index.motion | 170 |
| abstract_inverted_index.remain | 5 |
| abstract_inverted_index.system | 81 |
| abstract_inverted_index.target | 1 |
| abstract_inverted_index.vision | 192 |
| abstract_inverted_index.visual | 43 |
| abstract_inverted_index.within | 166, 180 |
| abstract_inverted_index.(6-DOF) | 109 |
| abstract_inverted_index.Average | 150 |
| abstract_inverted_index.YOLOv5s | 157 |
| abstract_inverted_index.address | 24 |
| abstract_inverted_index.channel | 49 |
| abstract_inverted_index.complex | 35 |
| abstract_inverted_index.enhance | 72 |
| abstract_inverted_index.feature | 73 |
| abstract_inverted_index.maximum | 119 |
| abstract_inverted_index.module. | 52 |
| abstract_inverted_index.network | 69 |
| abstract_inverted_index.orchard | 14 |
| abstract_inverted_index.picking | 178 |
| abstract_inverted_index.precise | 89 |
| abstract_inverted_index.reaches | 174 |
| abstract_inverted_index.robotic | 9, 110 |
| abstract_inverted_index.robots. | 200 |
| abstract_inverted_index.spatial | 90 |
| abstract_inverted_index.success | 172 |
| abstract_inverted_index.system. | 105 |
| abstract_inverted_index.through | 92 |
| abstract_inverted_index.working | 120 |
| abstract_inverted_index.Accurate | 0 |
| abstract_inverted_index.achieves | 88, 128 |
| abstract_inverted_index.acquires | 83 |
| abstract_inverted_index.baseline | 156 |
| abstract_inverted_index.clutter. | 22 |
| abstract_inverted_index.compared | 153 |
| abstract_inverted_index.exhibits | 112 |
| abstract_inverted_index.improved | 41 |
| abstract_inverted_index.in-range | 137 |
| abstract_inverted_index.locating | 30 |
| abstract_inverted_index.occluded | 76 |
| abstract_inverted_index.planning | 171 |
| abstract_inverted_index.proposed | 104 |
| abstract_inverted_index.proposes | 39 |
| abstract_inverted_index.provides | 187 |
| abstract_inverted_index.solution | 194 |
| abstract_inverted_index.specific | 60 |
| abstract_inverted_index.targets. | 77 |
| abstract_inverted_index.visually | 34 |
| abstract_inverted_index.Precision | 151 |
| abstract_inverted_index.algorithm | 45 |
| abstract_inverted_index.attention | 50 |
| abstract_inverted_index.completed | 179 |
| abstract_inverted_index.effective | 191 |
| abstract_inverted_index.efficient | 48 |
| abstract_inverted_index.matrices. | 95 |
| abstract_inverted_index.occlusion | 19 |
| abstract_inverted_index.algorithm. | 158 |
| abstract_inverted_index.challenges | 7 |
| abstract_inverted_index.confidence | 130 |
| abstract_inverted_index.controlled | 165 |
| abstract_inverted_index.coordinate | 93 |
| abstract_inverted_index.difficulty | 26 |
| abstract_inverted_index.harvesting | 11, 199 |
| abstract_inverted_index.impressive | 136 |
| abstract_inverted_index.integrated | 58 |
| abstract_inverted_index.operation, | 79 |
| abstract_inverted_index.conditions, | 36 |
| abstract_inverted_index.demonstrate | 99 |
| abstract_inverted_index.development | 197 |
| abstract_inverted_index.evaluations | 98 |
| abstract_inverted_index.identifying | 28 |
| abstract_inverted_index.improvement | 146 |
| abstract_inverted_index.information | 86 |
| abstract_inverted_index.operational | 115 |
| abstract_inverted_index.positioning | 161 |
| abstract_inverted_index.recognition | 2, 44, 139, 193 |
| abstract_inverted_index.significant | 6 |
| abstract_inverted_index.ECA-enhanced | 125 |
| abstract_inverted_index.YOLOv5-based | 42 |
| abstract_inverted_index.architecture | 70 |
| abstract_inverted_index.consistently | 164 |
| abstract_inverted_index.end-effector | 160 |
| abstract_inverted_index.environments | 15 |
| abstract_inverted_index.experimental | 97 |
| abstract_inverted_index.localization | 4, 91 |
| abstract_inverted_index.representing | 143 |
| abstract_inverted_index.unstructured | 13 |
| abstract_inverted_index.Comprehensive | 96 |
| abstract_inverted_index.characterized | 16 |
| abstract_inverted_index.effectiveness | 101 |
| abstract_inverted_index.incorporating | 46 |
| abstract_inverted_index.strategically | 57 |
| abstract_inverted_index.representation | 74 |
| abstract_inverted_index.simultaneously | 82 |
| abstract_inverted_index.transformation | 94 |
| abstract_inverted_index.custom-designed | 107 |
| abstract_inverted_index.six-degree-of-freedom | 108 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.26551841 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |