DeepMind’s AI uses aerial and ground-view data to navigate unseen areas

Might street-navigating AI be able to traverse previously unseen neighborhoods given sufficient training data? That’s what scientists at Google parent company Alphabet’s DeepMind investigate in a newly published paper (“Cross-View Policy Learning for Street Navigation“) on the preprint server Arxiv.org. In it, they describe transferring an AI policy trained with a ground-view corpus to target parts of a city using top-down visual information, an approach they say results in better generalization.