DEVICE AND METHOD FOR CONTROLLING A ROBOT DEVICE

A method for training a robot device controller is described comprising training a neural network comprising an encoder network, a decoder network and a policy network, such that, for each of a plurality of digital training input images, the encoder network encodes the digital training input image to a feature in a latent space, the decoder network determines, from the feature, for each of a plurality of areas shown in the digital training input image, whether the area is traversable and information about the distance between the viewpoint of the digital training input image and the area and the policy model determines, from the feature, control information for controlling movement of a robot device wherein at least the policy model is trained in a supervised manner using control information ground truth data of the digital training input images.