Natalia Calvo

My name is Natalia Calvo and I am from Colombia. I received my bachelor’s degree in Mechatronics Engineering from the “Nueva Granada” Military University (Bogota, Colombia ). During three years I worked in the Oil & Gas field as a project engineer on Automation and Control. Later, inspired to open an innovative and technological gate in my country, I launched my start-up focused on bringing support and robotics platform supplies such as mobile and haptic robotics, especially to educational institutions and universities. The result of that experience took me in 2016 to Italy to continue my postgraduate education carrying out the Master in Robotics Engineering at the University of Genoa, under the scholarship program promoted by the Ministry of Foreign Affairs and International Cooperation of Italy. This experience has allowed me to start studying how HRI may open the door to create systems that may assist humans in a large variety of fields. Currently, I am a visiting researcher at Keio University (Tokyo, Japan) studying different models focused on how robots can proactively act to the human behavior and its actions by exploiting intention inference so that interactions become more natural and user-friendly.

My research interest is mainly focused on exploiting machine learning techniques for bio-inspired behaviors. My fields of application lie on manipulation tasks, speech recognition interfaces, computer vision, and social robotics.

Recent research identifies trust as one of the key challenges in socially assistive robotics19. This ESR project will explore effects of robot embodiment on human perception of robot trustworthiness in an educational scenario with a socially assistive robot tutor. This requires (1) the investigation of social cues associated with perception of trust in human-human interactions, and specifically in a learning context, (2) the implementation of multimodal trustworthy behaviours in human-robot interactions in an educational scenario, and (3) the design of user studies to assess people’s trust towards a robot tutor. This will be done across different embodiments, for example robots with a more mechanical appearance and robots that are more human-like. A specific focus will be the investigation of perception of trust in presence of mixed embodiments (i.e., robotic and virtual), by exploiting platforms such as the Furhat robot. In order to identify synergies between robot appearance and behaviours and their effect on the perception of robot trustworthiness, a number of educational scenarios with a robotic tutor over different temporal scales will be designed, including (1) first impressions, (2) short encounters, and (3) long-term interactions.