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TACET: Context-Appropriate Acoustic-Social Navigation for Quadrupeds

A robotic hand reaching into a digital network on a blue background, symbolizing AI technology.
Illustrative photo.Photo by Tara Winstead on Pexels

What happened

arXiv:2610.03828v1 Announce Type: new Abstract: Quadruped robots entering hospitals, care homes, and quiet offices must be context-appropriate not only in where they move but in how loudly they move: a legged robot's locomotion noise, dominated by foot-ground impacts, is itself a social variable. The project page is available at https://rcilab.khu.ac.kr/tacet/.

Prior social navigation respects human space but treats the robot as acoustically uniform, while quiet-locomotion methods reduce noise to an operator-specified, context-blind level. The same token conditions both a social costmap (where to go) and a quiet locomotion policy (how loudly to move), while a structured out-of-view memory keeps recently seen people in the reasoner's context after they leave the camera view.

Sources & evidence