Mixed-Initiative in Human Augmented Mapping

In scenarios that require a close collaboration and knowledge transfer between inexperienced users and robots, the "learning by interacting" paradigm goes hand in hand with appropriate representations and learning methods. In this paper we discuss a mixed initiative strategy for robotic learning by interacting with a user in a joint map acquisition process. We propose the integration of an environment representation approach into our interactive learning framework. The environment representation and mapping system supports both user driven and data driven strategies for the acquisition of spatial information, so that a mixed initiative strategy for the learning process is realised. We evaluate our system with test runs according to the scenario of a guided tour, extending the area of operation from structured laboratory environment to less predictable domestic settings.