Over the past decades, the number of robots deployed in museums, trade shows and exhibitions have grown steadily. This new application domain has become a key research topic in the robotics community. Therefore, new robots are designed to interact with people in these domains, using natural and intuitive channels. Visual perception and speech processing have
to be considered for these robots, as they should be able to detect people in their environment, recognize their degree of accessibility and engage them in social conversations. They also need to safely navigate around dynamic, uncontrolled environments. They must be equipped with planning and learning components, that allow them to adapt to different scenarios. Finally, they must attract the attention of the people, be kind and safe to interact with. In this paper, we describe our experience with Gualzru, a salesman robot endowed with the cognitive architecture RoboCog. This architecture synchronizes all previous processes in a social
robot, using a common inner representation as the core of the
system. The robot has been tested in crowded, public daily life
environments, where it interacted with people that had never seen
it before nor had a clue about its functionality. Experimental
results presented in this paper demonstrate the capabilities of
the robot and its limitations in these real scenarios, and define
future improvement actions.
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