AGROBOT: An Autonomous Robotics System for Automated weed detection and eradication

The research project involves three interns collaborating on an innovative solution to improve farm management by automating weed control. Intern #1 is tasked with developing a smart system that uses machine learning and
computer vision to distinguish between crops and weeds, ensuring the robot can identify what needs to be removed without damaging valuable plants. The other two students will focus on the robot’s movement and
operation: one will refine how the robot’s arms move precisely to target and eliminate weeds based on the identifications made by the first student’s system. The second will work on optimizing the robot’s ability to navigate
and plan its actions in the dynamic outdoor environment of a farm. This collaborative effort aims to create a robot that can autonomously keep fields free of weeds, reducing the need for chemical herbicides and manual labor.
For the industry partner, this project promises a state-of-the-art agricultural tool that enhances efficiency, sustainability, and crop yield, potentially transforming modern precision farming practices.

Faculty Supervisor:

Mehrdad Saif

Student:

Partner:

BHF Agrobot

Discipline:

Engineering

Sector:

Agriculture; Manufacturing

University:

University of Windsor

Program: