Pedestrian Inertial Navigation: An Overview of Model and Data-Driven Approaches
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Abstract (arXiv)
The task of indoor positioning is fundamental to several applications, including navigation, healthcare, location-based services, and security. An emerging field is inertial navigation for pedestrians, which relies only on inertial sensors for positioning. In this paper, we present inertial pedestrian navigation models and learning approaches. Among these, are methods and algorithms for shoe-mounted inertial sensors and pedestrian dead reckoning (PDR) with unconstrained inertial sensors. We also address three categories of data-driven PDR strategies: activity-assisted, hybrid approaches, and learning-based frameworks.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 31 Jul 2024.
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Citing papers per year: 2025: 4.
4 papers.
- 2025MoRPI-PINN: A Physics-Informed Framework for Mobile Robot Pure Inertial Navigationcited by 3
- 2025On Neural Inertial Classification Networks for Pedestrian Activity Recognitioncited by 2
- 2025Diffusion-Driven Inertial Generated Data for Smartphone Location Classificationcited by 0
- 2025ICD-Net: Inertial Covariance Displacement Network for Drone Visual-Inertial SLAMcited by 0
- 2025ICD-Net: Inertial Covariance Displacement Network for Drone Visual-Inertial SLAM13 Nov 2025
- 2025MoRPI-PINN: A Physics-Informed Framework for Mobile Robot Pure Inertial Navigation24 Jul 2025
- 2025Diffusion-Driven Inertial Generated Data for Smartphone Location Classification20 Apr 2025
- 2025On Neural Inertial Classification Networks for Pedestrian Activity Recognition23 Feb 2025