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arXiv · 2604.06382

Designing Privacy-Preserving Visual Perception for Robot Navigation Based on User Privacy Preferences

Xuying Huang·Sicong Pan·Delphine Reinhardt·Maren Bennewitz
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Abstract

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.

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Xuying Huang, Sicong Pan, Delphine Reinhardt, Maren Bennewitz. 2026-04-07. Designing Privacy-Preserving Visual Perception for Robot Navigation Based on User Privacy Preferences. https://arxiv.org/abs/2604.06382

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