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This project focuses on developing a robotic arm manipulator capable of accurately cutting plant leaves for genetic analysis, improving the efficiency and precision of agricultural plant research. In current studies, researchers must manually cut leaves from hundreds of plants, a time-consuming process that introduces inconsistencies due to varying plant conditions over time. Automating this task will allow for faster, more reliable, and standardized sample collection, reducing human error and ensuring that all plants are processed under the same conditions.
To achieve this, the project will utilize an RGB-vision based system to help the robot accurately identify and target plant stems, which are too thin to be reliably detected by standard depth sensors. The robotic manipulator will need to operate with high accuracy, ensuring precise cuts without damaging the plant or disrupting the overall workflow.
By advancing robotic automation in life science research, this project will contribute to more efficient agricultural studies, particularly in understanding plant responses to drought. The work will also help improve laboratory automation by developing new methods for robotic control and motion planning. This collaboration will provide valuable insights into automation for plant science and precision agriculture, benefiting research efforts in both robotics and biology.
Arthur Chan
Osaka University
Engineering
Education
University of Toronto
Globalink Research Award
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