Neuro-robotics as a tool to understand the brain
To understand brains, we need to start from the simplest animals: take for example the worm C. elegans with only 350 neurons, able to look for food, remember food locations and mate. Brains originally evolved for movement: consider as an example phototaxis, the movement away or towards a stimulus or light that can be easily implemented with a robot by directly connecting sensors and motors. These behaviors are considered to be reactive and a direct mapping from sensors to actuation. What we want to do in this project is to use biological principles to map simple and complex behaviors into synthetic systems such as robots.
By following the structure of a neuro-biological control strategy based on a biologically based control Architecture developed at SPECS called DAC (Distributed Adaptive Control), we will learn how to implement a series of increasingly complex behavioral tasks such as a foraging… By using robots, you can teach them to search for food like animals do!
Students that join this project will experience how to build new behaving artefacts using state of art technology and knowledge in neuroscience, robotics and artificial intelligent, really embedded in a transdisciplinary environment.
In this course, we will use mobile 3D printed robots to address how we can build up complex behaviors introducing learning and memory into play. Students will be able to add more complex layers of behavior following the structure of the DAC architecture, which assumes that behavior is organized in layers from reactive, to adaptive (simplest learning) and contextual (including memory and learning).
Biology, mathematics, physics, computer sciences, robotics, artificial intelligence