Item Identification for Robotic Pick and Place Applications

This research project aims to develop a robot pick and place model that can be used in Kindred AI’s robotic arms to improve efficiency and reduce production costs. The intern will work closely with the partner organization’s experts in computer vision and MLOp to design and build new models, modify existing ones, and experiment with them on robotic arms. The project will benefit Kindred AI by enhancing its product offerings and increasing their competitiveness in the market. Additionally, this research will contribute to the advancement of robotics technology in Canada, which can potentially have significant implications for various industries.

Faculty Supervisor:

Igor Gilitschenski

Student:

Partner:

Kindred AI

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program: