The Un-Kidnappable Robot: Acoustic Localization of Sneaking People
Yang, Mengyu, Grady, Patrick, Brahmbhatt, Samarth, Vasudevan, Arun Balajee, Kemp, Charles C., Hays, James
–arXiv.org Artificial Intelligence
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
arXiv.org Artificial Intelligence
Oct-5-2023
- Genre:
- Research Report (0.40)
- Technology:
- Information Technology > Artificial Intelligence > Robots (1.00)