Methods and system for goal-conditioned exploration for object goal navigation

Abstract

In state of the art methods for object goal navigation, scene understanding is implicit in their goal oriented exploration policies. Implicit scene understanding coupled with navigation is shown to be specific to tasks for which training is done and not generalizable to new tasks. Thus, embodiments of present disclosure propose a method of goal-conditioned exploration wherein scene understanding is decoupled from the exploration policies. Here, the scene understanding required for navigation is provided by a region classification network that is trained using semantic graphs representing the scene and agent can be navigated towards the goal either by using any state of the art pure exploration policies or by traversing through potential sub-goals identified based on a Co-occurrence Likelihood score calculated by using predictions from the region classification network. Hence, the method of present disclosure can be easily generalized to new tasks and new environments.