In this paper, we propose a system for robust and flexible visual gesture recognition on a mobile robot for domestic service robotics applications. This adds a simple yet powerful mode of interaction, especially for the targeted user group of laymen and elderly or disabled people in home environments. Existing approaches often use a monolithic design, are computationally expensive, rely on previously learned (static) color models, or a specific initialization procedure to start gesture recognition. We propose a multi-step modular approach where we iteratively reduce the search space while retaining flexibility and extensibility. Building on a set of existing approaches, we integrate an on-line color calibration and adaptation mechanism for hand detection followed by feature-based posture recognition. Finally, after tracking the hand over time we adopt a simple yet effective gesture recognition method that does not require any training.