Gustavo Pérez Fuentevilla

Sun, 01 Oct 2023 00:00:00 +0000

Gustavo is a current PhD student in the Department of Industrial Engineering. His research work and experience includes mobile manipulation control design, analysis, and coordination. Currently working in active sensing algorithms for collaborative robots, safe motion planning and ergodic control. One of his main interests and motivation is combining classical design with novel AI approaches for robotic issues.

MAGICIAN

Sun, 01 Oct 2023 00:00:00 +0000

This is a research and innovation project funded by Horizon Europe. Website: https://magician-project.eu/.

4-year EU project: October 2023-September 2027
11 consortium partners from 7 countries across Europe coordinated by Università di Trento
1 Automotive Use Case and extension of Use Cases through 2 Open Calls

Vision

MAGICIAN will develop robotic solutions to classify and rework defects from semi-finished products autonomously before the finalization of product aesthetics.

These solutions are designed to be modular, applicable to various manufacturing fields, reducing physical strain and enhancing safety for human operators.

Challenges

Consumers increasingly expect manufacturing products to be free of defects which sets high standards for the production process. However, associated working processes are physically and cognitively demanding for workers and executed in a potentially hazardous environment.

Solutions

Two modular robotic solutions:

a sensing robot for defect analysis (SR)
a cleaning robot for reworking defects (CR)

Both robots will use AI modules to perform associated operations. Data needed for these AI modules will be gathered by learning from workers operating on semi-finished products.

Human-centred approach: MAGICIAN applies a human-centred design strategy to shape the progress of automation and human-robot collaboration in manufacturing towards an emphasis on trust, empathy, and ethics.

Use Cases: MAGICIAN solutions will be tested in an automotive manufacturing use case. Both robots will be coupled with human operators during the testing to ensure trust-based human-robot collaboration. Additional use cases will be engaged through two Open Calls.

Impact