  In this article, we present a new scheme that approximates unknown
sensorimotor models of robots by using feedback signals only. The formulation
of the uncalibrated sensor-based regulation problem is first formulated, then,
we develop a computational method that distributes the model estimation problem
amongst multiple adaptive units that specialise in a local sensorimotor map.
Different from traditional estimation algorithms, the proposed method requires
little data to train and constrain it (the number of required data points can
be analytically determined) and has rigorous stability properties (the
conditions to satisfy Lyapunov stability are derived). Numerical simulations
and experimental results are presented to validate the proposed method.
