AUTOMATIC LEARNING OF RELEVANT ACTIONS IN MOBILE ROBOTS

Described is a system and method for robotic perception and action. The system includes a mobile autonomous platform programmed to receive a visual input related to an environment and perform a movement sequence that affects the environment based on the visual input. A neural network is in communication with the mobile autonomous platform. The neural network includes a vision autoencoder trained, based on movements of the mobile autonomous platform, to encode visual features of an object in the visual input onto a visual latent space. In addition, the neural network includes an action autoencoder trained, based on movements of the mobile autonomous platform, to encode action features of the movement sequence onto an action latent space. The neural network also includes a mapping layer between the vision autoencoder and the action autoencoder. The mapping layer decodes the visual inputs into an action output of the mobile autonomous platform.