The Un-Kidnappable Robot: Acoustic Localization of Sneaking People
Mengyu Yang Patrick Grady Samarth Brahmbhatt Arun Balajee Vasudevan Charles C. Kemp James Hays
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. We collect a robotic dataset of high-quality 4-channel
audio paired with 360 degree RGB data of people moving in different indoor
settings. We train models that predict if there is a moving person nearby and
their location using only audio. We implement our method on a robot, allowing
it to track a single person moving quietly with only passive audio sensing. For
demonstration videos, see our project page:
https://sites.google.com/view/unkidnappable-robot