UBC AgroBot Design Team

We are a diverse team of students from across different engineering disciplines. With a shared passion for innovation and technology, we hope to explore robotics in farming, contributing to the future of agriculture in transitioning from human labour to full automation.

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Our Project

As the world population grows, climate change continues and reliable human labour becomes increasingly expensive, we must find more efficient and sustainable ways to grow food and sustain ourselves. The UBC AgroBot team will be building a fully autonomous robot capable of analyzing its environment and performing targeted weeding, fertilizing and soil analysis though the use of advanced robotics, image recognition and machine learning.

Image Recognition

We intend to use the Tensorflow object identification module, training and fine-tuning our own recognition model for crops and weeds

Advanced Robotics

We will be engineering the specific mechanics of the AgroBot, designing the chasis and exterminating mechanism, ultimately integrating them with the Robot Operating System

Machine learning

We will utilize the latest technology in machine learning to help us construct an autonomous image recognition system and a navigation system

The Challenge

AGgrowBOT @ Purdue University

This project will be competing in the AGgrowBOT challenge at Purdue University, Indiana. This competition attracts many teams from companies and universities across North America. The objectives of the competition are to create an autonomous machine capable of navigating a wheat field to identify weeds and analyze crop health.

Upon identification of the wheat plant, the machine should determine if the plant is healthy or in distress which requires fertilizer to be applied by the machine. Upon identification of a weed, the machine should eradicate the weed chemically and/or mechanically. The competition will be judged by reputable members of the agricultural technology industry, such as The Climate Corporation (Monsanto), and Blue River Technology.

The Team

Team Photo

Navigation System Team

The navigation team is dedicated towards the realization of an automatic navigation and positioning system for the robot

Image Recognition System Team

The image recognition team works with algorithms closely, in order to train an efficient and accurate crop recognition model

Our Subteams

Chassis Design Team

The chassis team will design the basic frame that the AgroBot runs on, giving AgroBot the ability to steer and maneuver

Exterminating Mechanisms Team

The exterminating mechanisms team devises the optimal strategy to exterminating weed and fertilizing crops, minimizing chemical use

Latest Blogs

Learn about our newest progress and current team status by reading our official blogs.

End of Year Announcement

May12th, 2020

This year has been a meaningful and successful debut for AgroBot! We have worked hard throughout the year to build our very first agricultural robot prototype...

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Sponsor Info

AgroBot reaches out to a wide range of audience through social media, outreach events and competition. Posts will be made on a continuous basis on project updates and competition status while providing coverage for our partnering sponsors. Participation in the agBot Challenge will also provide us and our sponsors great exposure to the agricultural and tech sector in academia, and industry.


  • Logo on website
  • Logo on promotional materials


  • Logo on website
  • Logo on promotional materials
  • Exclusive tour with the team


  • Logo on website & promotional materials
  • Logo on apparel
  • Exclusive tour with the team
  • Social media coverage throughout the year


  • Logo on website, promotional materials, and apparel
  • Exclusive tour with the team
  • Social media coverage throughout the year
  • Logo on competing robot

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