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Equipping autonomous robots with vision sensors provides a multitude of advantages by simultaneously bringing up difficulties with regard to different illumination conditions. Furthermore, especially with service robots, the objects to be handled must somehow be learned for a later manipulation. In this paper we summarise work on combining two different vision sensors, namely a laser range scanner and a monocular colour camera, for shape-capturing, detecting and tracking of objects in cluttered scenes without the need of intermediate user interaction. The use of different sensor types provides the advantage of separating the shape and the appearance of the object and therefore overcome the problem with changing illumination conditions. We describe the framework and its components of visual shape-capturing, fast 3D object detection and robust tracking as well as examples that show the feasibility of this approach.

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