In the last decades, robotics has exerted an important role in the research on diverse knowledge domains, such as, artificial intelligence, biology, neuroscience and psychology. In particular, the study of knowledge representation and thinking, has led to the proposal of cognitive architectures; capturing essential structures and processes of cognition and behavior. Robotists have also attempted to design automatic systems using these proposals. Though, certain difficulties have been reported for obtaining efficient low-level processing while sensing or controlling the robot. The main challenges involve the treatment of the differences between the computational paradigms employed by the cognitive and the robotic architectures. The objective of this work, is to propose a methodology for designing robotic systems capable of decision making and learning when executing manipulative tasks. The development of a system called the Cognitive Reaching Robot (CRR) will be reported. CRR combines the advantages of using a psychologically-oriented cognitive architecture, with efficient low-level behavior implementations through the visual servoing control technique.