Anchored by Sound: Indoor Trajectory Mapping with Activity-Driven Audio Anchors

Indoor trajectory mapping is essential for applications such as health status monitoring, context-aware computing, and tracking systems. These applications often require accurate location information in environments where the Global Navigation Satellite System (GNSS) is unavailable or unreliable. Infrastructure-free approaches, such as inertial sensor-based Pedestrian Dead Reckoning (PDR), have gained popularity due to their ease of deployment and low cost. However, a key limitation of PDR is not only its susceptibility to cumulative drift over time but also its lack of absolute position references, which prevents reliable alignment of the trajectory with real-world coordinates. To address this challenge, we propose an activity-driven audio-IMU fusion solution that uses Factor Graph Optimization (FGO) to accurately reconstruct indoor walking trajectories on a room-scale floor plan. Specifically, we use two fixed microphone arrays to estimate absolute coordinates from activity-driven audio events. These events act as sparse, high-confidence anchors to map PDR trajectories. We validate our system through experiments in a 6 m × 6 m room. The proposed fusion solution achieves a mean positioning error of 0.31 m, with 68% and 95% of errors below 0.38 m and 0.53 m, respectively. The results demonstrate the potential of sparse, activity-driven audio anchoring to improve infrastructure-free indoor trajectory mapping.