Data-driven autonomous robotic food handling

The project will develop new reliable data-driven control algorithms for robotic manipulation. Technologies for low-cost handling of food products will be explored in this project. Some low-cost articulated robotic arms equipped with grasping end-effectors will be developed and tested with the reasonable speed, accuracy, and reliability.

The research will focus on reliable data-driven control algorithms for food manipulation. The student will develop adaptive impedance control through a path of increasing complexity, starting from basic energy-aware control algorithms to a reliable adaptive control framework. This will be paired with mechanical design and prototyping, with the goal of co-designing control algorithms and (compliant, tuneable) hardware. The research will be validated on a commercial robotic system provided by RT Corp.

The student will have full access to all teaching courses at undergraduate, master, and PhD level, in engineering and wider domains (communication, management, etc.). The student will also learn from a large body of activities at the Control Laboratory, at the Bio-Inspired Robotic Laboratory, and at the Observatory for Human-Machine Collaboration.