The Un-Kidnappable Robot: Acoustic Localization of Sneaking People

How easy is it to sneak up on a robot? We examine whether we can detect people using only the incidental sounds they produce as they move, even when they try to be quiet. To do so, we first collect a robotic dataset of high-quality 4-channel audio paired with 360° RGB data of people moving in different indoor settings. Using this dataset, we train models to predict if there is a moving person nearby and then their location using only audio. We implement our method on a robot, allowing it to track a single person moving quietly using only passive audio sensing. For demonstration videos, see our project page.