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This paper investigates user preferences for privacy-preserving visual perception in robot navigation through two user studies, revealing a preference for visual abstractions and capture-time low-resolution preservation. The studies demonstrate that preferred RGB resolution is contingent on both desired privacy level and robot proximity. Based on these findings, the authors propose a user-configurable distance-to-resolution privacy policy for robot visual navigation, aligning technical design with user-centric privacy needs.
People want blurry robot vision, but *how* blurry depends on how close the robot is and how nosy they think it's being.
Visual navigation is a fundamental capability of mobile service robots, yet the onboard cameras required for such navigation can capture privacy-sensitive information and raise user privacy concerns. Existing approaches to privacy-preserving navigation-oriented visual perception have largely been driven by technical considerations, with limited grounding in user privacy preferences. In this work, we propose a user-centered approach to designing privacy-preserving visual perception for robot navigation. To investigate how user privacy preferences can inform such design, we conducted two user studies. The results show that users prefer privacy-preserving visual abstractions and capture-time low-resolution preservation mechanisms: their preferred RGB resolution depends both on the desired privacy level and robot proximity during navigation. Based on these findings, we further derive a user-configurable distance-to-resolution privacy policy for privacy-preserving robot visual navigation.
