TomatoPoseNet: An Efficient Keypoint-Based 6D Pose Estimation Model for Non-Destructive Tomato Harvesting

TomatoPoseNet: An Efficient Keypoint-Based 6D Pose Estimation Model for Non-Destructive Tomato Harvesting

The non-destructive harvesting of fresh tomatoes with agricultural robots requires the robotic arm to approach the fruit with the correct posture to ensure successful harvesting. However, this process faces significant challenges due to the small size of fruit pedicels, cluttered environments, and v...

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Bibliographic Details
Main Authors: Jipeng Ni, Licheng Zhu, Lizhong Dong, Ruixue Wang, Kaikang Chen, Jianbo Gao, Wenbei Wang, Liming Zhou, Bo Zhao, Jiacheng Rong, Zhenhao Han, Kunlei Lu, Xuguang Feng
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Agronomy
Subjects:
agricultural robotics
tomato harvesting
pose estimation
keypoint detection
non-destructive harvesting
deep learning
Online Access:https://www.mdpi.com/2073-4395/14/12/3027
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