Occluded Apple Fruit Detection and Localization with a Frustum-Based Point-Cloud-Processing Approach for Robotic Harvesting

Occluded Apple Fruit Detection and Localization with a Frustum-Based Point-Cloud-Processing Approach for Robotic Harvesting

Precise localization of occluded fruits is crucial and challenging for robotic harvesting in orchards. Occlusions from leaves, branches, and other fruits make the point cloud acquired from Red Green Blue Depth (RGBD) cameras incomplete. Moreover, an insufficient filling rate and noise on depth image...

Full description

Bibliographic Details
Main Authors: Tao Li, Qingchun Feng, Quan Qiu, Feng Xie, Chunjiang Zhao
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Remote Sensing
Subjects:
agricultural robot
deep learning
fruit detection
point cloud
apple-harvesting robot
RGBD camera
Online Access:https://www.mdpi.com/2072-4292/14/3/482

Internet

https://www.mdpi.com/2072-4292/14/3/482

Similar Items