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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2026
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2604.06382 |
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| _version_ | 1866917389467123712 |
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| author | Huang, Xuying Pan, Sicong Reinhardt, Delphine Bennewitz, Maren |
| author_facet | Huang, Xuying Pan, Sicong Reinhardt, Delphine Bennewitz, Maren |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_06382 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Designing Privacy-Preserving Visual Perception for Robot Navigation Based on User Privacy Preferences Huang, Xuying Pan, Sicong Reinhardt, Delphine Bennewitz, Maren Robotics 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. |
| title | Designing Privacy-Preserving Visual Perception for Robot Navigation Based on User Privacy Preferences |
| topic | Robotics |
| url | https://arxiv.org/abs/2604.06382 |