A new approach of robotics perception, rooted in the sensorimotor paradigm, is proposed in this paper. Making systems able to autonomously adapt themselves to changes in their own body or in their environment is still a challenging task, questioning a lot of different scientific communities. But many works propose either sophisticated adaptive model-based or learning-based techniques as a solution. Recent contributions have shown that it is possible for an agent to discover the structure of its interaction with the environment or its own body via the so-called sensorimotor flow. The presented work is based in this idea, and a method for the building of an internal representation of its sensorimotor interaction is proposed. Importantly, it does not require any a priori knowledge nor model. A careful mathematical formalization is outlined, together with simulations demonstrating the effectiveness of the approach. Several cases are considered allowing a general discussion. Moreover, plausibility of the internal sensorimotor representation is highlighted by showing that it is possible to consider motion planning directly from it.