Before revision:  We introduce a reinforcement learning approach to audio-visual navigation with two key novel elements  1) audio-visual waypoints that are dynamically set and learned end-to-end within the navigation policy, and 2) an acoustic memory that provides a structured, spatially grounded record of what the agent has heard as it moves.
After revision:  We introduce a reinforcement learning approach to audio-visual navigation with two key novel elements 1) waypoints that are dynamically set and learned end-to-end within the navigation policy, and 2) an acoustic memory that provides a structured, spatially grounded record of what the agent has heard as it moves.