Autonomous Development of Active Binocular and Motion Vision Through Active Efficient Coding.

ABSTRACT: We present a model for the autonomous and simultaneous learning of active binocular and motion vision. The model is based on the Active Efficient Coding (AEC) framework, a recent generalization of classic efficient coding theories to active perception. The model learns how to efficiently encode the incoming visual signals generated by an object moving in 3-D through sparse coding. Simultaneously, it learns how to produce eye movements that further improve the efficiency of the sensory coding. This learning is driven by an intrinsic motivation to maximize the system's coding efficiency. We test our approach on the humanoid robot iCub using simulations. The model demonstrates self-calibration of accurate object fixation and tracking of moving objects. Our results show that the model keeps im

SUBMITTER: Lelais A 

PROVIDER: S-EPMC6646586 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature