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Inspired by child development and brain research, we introduce a computational framework which integrates robotic active vision and reaching. Essential elements of this framework are sensorimotor mappings that link three different computational domains relating to visual data, gaze control, and reaching. The domain of gaze control is the central computational substrate that provides, first, a systematic visual search and, second, the transformation of visual data into coordinates for potential reach actions. In this respect, the representation of object locations emerges from the combination of sensorimotor mappings. The framework is tested in the form of two different architectures that perform visually guided reaching. Systematic experiments demonstrate how visual search influences reaching accuracy. The results of these experiments are discussed with respect to providing a reference architecture for developmental learning in humanoid robot systems.