Project Type: Graduate Student
Funds awarded in 2024: $21,465.00
Projected End Date: 08/31/2026
Grant Recipient:
University of Georgia
Region: Southern
State: Georgia
Graduate Student:
Major Professor:
Dr. Md Sultan Mahmud
University of Georgia
Description:
This journal article reviews recent advances in 3D sensing and perception for precision weed management, with a focus on sensing modalities, reconstruction pipelines, and context aware weed detection. The paper synthesizes current approaches used to acquire structural crop and weed information and evaluates their potential for improving selective, site specific weed control. It also identifies key technical challenges, research gaps, and future opportunities for integrating 3D perception into autonomous weed management systems. This publication provides researchers and agricultural engineers with a structured reference for developing more accurate and robust perception systems for precision weed control.
Type:
Peer-reviewed Journal Article
Target audiences:
Educators; Researchers
Ordering info:
Publication/product ID: S0168169925013250
This product is associated with the project "Development of an Autonomous Laser-Based Robotic System for Sustainable Weed Management in Vidalia Onions"
Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and should not be construed to represent any official USDA or U.S. Government determination or policy.