An Approach toward Self-organization of Artificial Visual Sensorimotor Structures

Living organisms exhibit a strong mutual coupling between physical structure and behavior. For visual sensorimotor systems, this interrelationship is strongly reflected by the topological organization of a visual sensor and how the sensor is moved with respect to the organism's environment. Here we present an approach which addresses simultaneously and in a unified manner i) the organization of visual sensor topologies according to given sensor-environment interaction patterns, and ii) the formation of motor movement fields adapted to specific sensor topologies. We propose that for the development of well-adapted visual sensorimotor structures, the perceptual system should optimize available resources to accurately perceive an observed phenomena, and at the same time, should co-develop sensory and motor layers such that the relationship between past and future stimuli is simplified on average. In a mathematical formulation, we implement this request as an optimization problem where the variables are the sensor topology, the layout of the motor space, and a prediction mechanism establishing a temporal relationship. We demonstrate that the same formulation is applicable for spatial self-organization of both, visual receptive fields and motor movement fields. The results demonstrate how the proposed principles can be used to develop sensory and motor systems with favorable mutual interdependencies.