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.
We intend to use the Tensorflow object identification module, training and fine-tuning our own recognition model for crops and weeds
We will be engineering the specific mechanics of the AgroBot, designing the chasis and exterminating mechanism, ultimately integrating them with the Robot Operating System
We will utilize the latest technology in machine learning to help us construct an autonomous image recognition system and a navigation system
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 navigation team is dedicated towards the realization of an automatic navigation and positioning system for the robot
The image recognition team works with algorithms closely, in order to train an efficient and accurate crop recognition model
The chassis team will design the basic frame that the AgroBot runs on, giving AgroBot the ability to steer and maneuver
The exterminating mechanisms team devises the optimal strategy to exterminating weed and fertilizing crops, minimizing chemical use
We are looking for highly motivated students with a passion for innovation and solving problems. This year, we will be picking up where we left off and continue working on our first weed exterminating robot. There is still a lot of design, prototyping, integration and testing to be done. Members will have the opportunity to go through the engineering design process and develop their own solutions to this unique challenge.
We will also be expanding UBC AgroBot with a new Hydroponics project. The Hydroponics project team will aim to develop autonomous hydroponic systems with the potential to be implemented throughout campus. More information coming soon.
We recruit first years to graduate students from all disciplines. Please refer to our blog posts for more information on each sub-team's recruitment details. You can also learn more about us on Imagine Day or feel free to reach out through email. Applications are now open.
*This year, we will be prioritizing remote working.
Learn about our newest progress and current team status by reading our official blogs.
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.