In this paper we consider the problem of sensorimotor coordination in a Bayesian framework. To this end we introduce a novel kind of Dynamic Bayesian Network serving as the core tool to integrate active vision and task-constrained motor behaviors. The proposed system is put into work by addressing the challenging task of realistic drawing performed by a robotic agent, namely a 7-DOF anthropomorphic manipulator. Simulation results are compared to those obtained by eye-tracked human subjects involved in drawing experiments.
['Ruben Coen Cagli', 'Paolo Napoletano', 'Paolo Coraggio', 'Giuseppe Boccignone', 'A. De Santis']
Sensorimotor coupling via dynamic bayesian networks