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On the influence of sensor morphology on sensory-motor coordination : an information theoretic view Technical Report

In developmental robotics, there is a lot of work related to learning, which focuses on how to enable robots with adaptive capabilities. However, there is not much understanding of how the morphology of sensors and actuators affects the learning process. By taking inspiration from the human vision system, we explore how the sensor integration, its morphology together with the body of the robot, are the conditions that enable infants, in the first months of life, to achieve behaviors such as attention, vergence, reaching and grasping. Hence the sensor morphology is an important aspect that can be exploited, first to reduce the amount of inputs without disrupting perception, and second it limits the possible actions and behaviors that enable the agent to learn whether an environment model or a specific task. In this report, we present an information theoretic analysis of three experiments showing how foveation and the creation of a single image from two images demand the vergence behavior as a mechanism to increase the information structure not just among the pixels in the image but also among the motor actions and the pixels, establishing the prerequisite for learning. We also speculate on the implications of our results for theories of human development.