Innovative integration of maturity detection and robotic technology for enhanced litchi harvesting
Abstract An integrated approach marries an optimized YOLOv7 deep learning model with a 6-axis robotic arm, featuring a novel end-effector design, to elevate automated litchi harvesting. The model, refined with ACmix attention and Focal-EIoU loss functions, adeptly identifies litchi maturity across diverse orchard settings, overcoming challenges like variable lighting and occlusions. Rigorous field validations and real-world applications demonstrate the system’s efficacy, with an 85.7% success rate in precisely harvesting mature litchis. This fusion of cutting-edge image recognition with strategic mechanical innovation effectively mitigates labor shortages and enhances productivity, marking a significant leap forward in orchard automation.
Authors
- Juntao Xiong (ORCID: https://orcid.org/0000-0002-1095-812X)
- Qiyin Huang (ORCID: https://orcid.org/0000-0001-9985-9146)
- Chengzhuo Zhou (ORCID: https://orcid.org/0000-0001-8656-3821)
- Xinjing Jiang
Institutions
- South China Agricultural University (CN)
Publication Details
- Journal
- Journal of Physics Conference Series
- Published
- 2024-09-01
- DOI
- https://doi.org/10.1088/1742-6596/2842/1/012074
- Primary Topic
- Industrial Vision Systems and Defect Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00