Evolutionary robotics

Summary

The course describes theories, methods, and technologies for designing robots and artificial systems inspired by evolution, development, and learning. It also shows how robotic models can help to understand biological systems. The course ends with a discussion of future bio-hybrid robots.

Content

Learning Prerequisites

Important concepts to start the course

Programming skills (Phython, Java, C++)

Learning Outcomes

By the end of the course, the student must be able to:

• Apply new tools for software and hardware engineering
• Translate acquired theoretical knowledge in practical implementations during laboratory sessions

Teaching methods

Lectures, software exercises, and exercises and project involving 3D printing, assembly, programming, and characterization of modular robot with neural controller.

Expected student activities

Attending lectures, asking critical questions, taking all exercises and completing assignments for the following week, forming groups and performing collaboratively project woth physical robots, writing and presenting project results

Assessment methods

Mini-project report/presentation + written exam

Supervision

Resources

Bibliography

Floreano, D. & Mattiussi, C. (2008) Bioinspired Artificial Intelligence. MIT Press (selected chapters)

Ressources en bibliothèque

• Bioinspired Artificial Intelligence / Floreano

Moodle Link

• https://go.epfl.ch/MICRO-515