Learning human-robots interactions
In this thesis the field of learning human-robotic interaction will be explored. To find the different challenges in this field a model of hide-and-seek will be developed, where the robot will be playing the seeker, and there will be one or more humans hiding. This game analyses a form of human-robot interaction, because (1) the robot wins by recognizing and approaching sufficiently the hider, and (2) the hider wins by arriving to the base without being caught by the robot, i.e. by avoiding the robot.
The work is under the scope of the following projects:
- CEEDS: The collective experience of empathic data systems (web)