Problem
Research questions and friction points this paper is trying to address.
privacy-preserving
visual perception
robot navigation
user privacy preferences
mobile service robots
Designing Privacy-Preserving Visual Perception for Robot Navigation Based on User Privacy Preferences
🤖 AI Summary
This study addresses privacy risks posed by mobile service robots that may capture privacy-sensitive visual information during navigation. It presents the first systematic integration of user privacy preferences into the design of robotic visual perception. Through two user studies, the authors uncover user preferences for visual abstraction and in-situ resolution reduction. Building on these insights, they propose a dynamic resolution control mechanism that adapts camera resolution based on distance to people and contextual privacy sensitivity levels. This mechanism enables configurable privacy-preserving policies, effectively enhancing privacy protection while maintaining robust navigation performance.
📝 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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
privacy-preserving visual perception
user-centered design
robot navigation
visual abstraction
distance-to-resolution policy
🔎 Similar Papers
No similar papers found.
