FlightMagNav: An Open Dataset and Probabilistic Map Learning and Validation Framework for Outdoor Magnetic Field-Based Positioning
To facilitate research on magnetic field-based positioning for aerial platforms operating close to the Earth's surface, an open dataset is presented with measurements collected using an unmanned aerial vehicle carrying two optically pumped magnetometers, a type of quantum magnetometer, and a global navigation satellite system-aided inertial navigation system.
ProofPaper ↗
Key points
- Magnetic field-based positioning is a resilient positioning technology that requires no external infrastructure and is hard to jam at scale.
- The dataset includes measurements for both magnetic-field map learning and validation.
- Along with the dataset, a probabilistic framework for magnetic-field map learning and validation is presented and used to illustrate how the dataset may be used.
- Finally, we outline research directions that may be explored using the dataset.
Sources (1)
- [1]FlightMagNav: An Open Dataset and Probabilistic Map Learning and Validation Framework for Outdoor Magnetic Field-Based PositioningarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 6, 06:43 PM
To facilitate research on magnetic field-based positioning for aerial platforms operating close to the Earth's surface, an open dataset is presented with measurements collected using an unmanned aerial vehicle carrying two optically pumped magnetometers, a type of quantum magnetometer, and a global navigation satellite system-aided inertial navigation system.
Magnetic field-based positioning is a resilient positioning technology that requires no external infrastructure and is hard to jam at scale.
Extractive summary: sentences quoted from the sources.