Welcome to the BRAIN Lab

The BRAIN Lab is  lab we aim to design and develop robots that learn to interact socially with humans and bring benefits to the society we live in, for example in application areas such as education, e-learning, healthcare and assistive technology. Learn more about us!

SCIENTIFIC CONTEXT and OBJECTIVES

The Brain Lab aims to make the interactions between humans and machines, in particular humanoid robots, simpler and more natural and to interpret the social behavior of users who interact with these machines by analyzing the enormous amount of data collected during the interaction both by the sensors on board the robot and by external or wearable sensors.

We mainly  focus on Cognitive Robotic, that is a subfield of Robotics concerned with equipping a robot with intelligent behavior by providing it with a computing architecture that allows it to learn and reason about how to behave in response to complex goals in a complex world. One of the laboratory's goals is to develop novel architectures and approaches to enhance robotic systems' "perception-understanding-action" cycle, drawing influence from human cognitive models.

Perception necessitates the processing of a huge volume of raw input from the actual world (for example, using computer vision algorithms) or biosignals obtained by wearable sensors.

Understanding is addressed by researching novel learning architectures based on the key paradigms of cognitive computing (neural networks, ontologies, and so on).

The Lab research aims to integrate fundamental cognitive aspects (meaning comprehension, learning, decision-making processes, and communication) with higher-level aspects such as emotions (affect computing), creativity (computational creativity), mental models, and motivations that have a strong influence on actions in real environments. 

The attention of the laboratory goes mainly in the direction of emotion recognition algorithms, which allow for a more in depth comprhension between humans and robots, helping structure even more natural and human-like behaviors.

The lab is also involved in research on brain models for motor control, sensori-motor coordination, and cognition in autonomous robots. Cognitive abilities, the same way they function in humans and other living beings, would help next-generation robots be persistent in their behavior and aware of themselves and their environment. Furthermore, they would allow the emotional state of the user who interacts with the robot to be monitored in order to adapt its behavior. 

Cognitive models require the integration of concepts from neurophysiology, neuroscience, developmental studies, and artificial intelligence with robotics. At the same time, such robotic implementations contribute to the experimental validation of biological models by giving them the possibility not only to describe biological solutions through biomimetic technologies but, more importantly, to explain why biological solutions have been modeled that way. Experiments are currently underway aimed at analyzing the brain dynamics triggered by the interaction between humans and robots.

Another important objective concerns the social interaction of the system through language processing, textual information analysis (social or semantic computing), and human-robot interaction models. 

The experiments concern both autonomous software systems such as chatbots and the latest generation of humanoid robotic platforms. The laboratory is dedicated to the study of the role that robotics plays in the field of cognitive and social sciences. It also promotes research of an experimental nature and is involved in numerous educational activities and relationships with the local area. In particular, the studies carried out in the laboratory aim to integrate robotics, the internet, cloud, mobile, and electronic technologies for the creation of new solutions valid for all sectors, from social robotics and assistance to health, agriculture, and logistics.

The main scientific challenges to improving the skills and capabilities of robotic systems revolve around human-machine interaction, both physical and cognitive, exploiting intelligent environments and reliable design.

The laboratory sites host robotic systems, audio-video systems for field research, devices for the creation of non-invasive brain-machine interfaces, IT spaces, and resources for the planning of research activities.

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