In swarm robotics multiple robots collectively solve problems by forming advantageous structures and behaviors similar to the ones observed in natural systems, such as swarms of bees, birds, or fish. However, the step to industrial applications has not yet been made successfully. Literature is light on real-world swarm applications that apply actual swarm algorithms. Typically, only parts of swarm algorithms are used which we refer to as basic swarm behaviors. In this paper we collect and categorize these behaviors into spatial organization, navigation, decision making, and miscellaneous. This taxonomy is then applied to categorize a number of existing swarm robotic applications from research and industrial domains. Along with the classification, we give a comprehensive overview of research platforms that can be used for testing and evaluating swarm behavior, systems that are already on the market, and projects that target a specific market. Results from this survey show that swarm robotic applications are still rare today. Many industrial projects still rely on centralized control, and even though a solution with multiple robots is employed, the principal idea of swarm robotics of distributed decision making is neglected. We identified mainly following reasons: First of all, swarm behavior emerging from local interactions is hard to predict and a proof of its eligibility for applications in an industrial context is difficult to provide. Second, current communication architectures often do not match requirements for swarm communication, which often leads to a system with a centralized communication infrastructure. Finally, testing swarms for real industrial applications is an issue, since deployment in a productive environment is typically too risky and simulations of a target system may not be sufficiently accurate. In contrast, the research platforms present a means for transforming swarm robotics solutions from theory to prototype industrial systems.

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Modern lifestyle has created a new species of tourist who makes several short city trips per year and uses high-tech equipment. LoL@ (local location assistant) is a location-based multimedia UMTS (universal mobile telecommunications system) application that aims at supporting this class of tourist. LoL@ offers maps, localization, and routing functionality, and speaker-independent speech input. To stay in contact with people at home a tour diary is offered. Technical constraints like limited bandwidth, connection loss, and varying localization accuracy have to be accounted for. Although the field trials have not been completed yet, it can already be seen that map representation on smart phones with small displays is feasible. Electronic tourist guide City guide Location-based service Mobile Internet Universal mobile telecommunications system (UMTS) gation and routing, multimodal interaction, and an electronic tour diary. Assumptions of tourist behavior were based on literature (Cheverst et al., 2000a; Long et al., 1996; Poslad et al., 2001) and currently available tools such as written tour guides (Polyglott, 2000) and electronic navigation tools (Durocher, 2000; Palmtop Software, 2002). Tourists are well-educated people who stay in the city for an extended weekend on a trip combining business and leisure and don't spend much time planning the trip beforehand. They are interested in exploring the city on foot by themselves-not bound by any schedule-using LoL@ as an "interactive version" of the classic printed guidebook.

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