The paper describes a multimodal scheme for humanrobot interaction suited for a wide range of intelligent service robot applications. Operating in unengineered, cluttered, and crowded environments, such robots have to be able to actively contact potential users in their surroundings and to oer their services in an appropriate manner. Starting from a real application scenario, the usage of a robot as mobile information kiosk in a home store, some reliable methods for vision-based interaction, noise analysis and speech output have been developed. These methods are integrated into a prototypical interaction cycle that can be assumed as a general approach to human-machine interaction. Experimental results demonstrate the strengths and weaknesses of the proposed methods.

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The paper presents vision-based robot navigation and user localization techniques of our long-term research project PERSES (PERsonal SErvice System), which aims to develop an interactive mobile shopping assistant that allows a continuous and intuitively understandable interaction with customers in a home store. Against this background, the paper describes a number of new or improved approaches, addressing challenges arising from the characteristics of the operation area, and from the need to continuously interact with users in a complex environment. With our approaches to vision-based or visually-controlled map building, self-localization and navigation as well as user localization and tracking, we want to make a contribution to the real-world suitability of interactive mobile service-robots in non-trivial application areas and demanding human-robot interaction scenarios.