Navig-AI-tion: Navigation by Contextual AI and Spatial Audio
This work addresses navigation challenges for visually impaired or audio-only users, but it is incremental as it builds on existing VLM and spatial audio technologies.
The paper tackled the problem of disorientation in audio-only walking navigation by integrating a Vision Language Model with spatial audio cues to provide landmark-anchored instructions and corrective directional signals, resulting in reduced route deviations in a user study with 12 participants compared to baseline systems.
Audio-only walking navigation can leave users disoriented, relying on vague cardinal directions and lacking real-time environmental context, leading to frequent errors. To address this, we present a novel system that integrates a Vision Language Model (VLM) with a spatial audio cue. Our system extracts environmental landmarks to anchor navigation instructions and, crucially, provides a directional spatial audio signal when the user faces the wrong direction, indicating the precise turn direction. In a user study (n=12), the spatial audio cue with VLM reduced route deviations compared to both VLM-only and Google Maps (audio-only) baseline systems. Users reported that the spatial audio cue effectively supported orientation and that landmark-anchored instructions provided a better navigation experience over audio-only Google Maps. This work serves as an initial look at the utility of future audio-only navigation systems for incorporating directional cues, especially real-time corrective spatial audio.