mlsanityData to 14 Oct 2026

Dynamic Sensor Matching based on Geomagnetic Inertial Navigation

arXiv 2208.06233 ↗First posted 12 Aug 2022cs.RO cs.AI cs.CVcited by 1

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Abstract (arXiv)

Optical sensors can capture dynamic environments and derive depth information in near real-time. The quality of these digital reconstructions is determined by factors like illumination, surface and texture conditions, sensing speed and other sensor characteristics as well as the sensor-object relations. Improvements can be obtained by using dynamically collected data from multiple sensors. However, matching the data from multiple sensors requires a shared world coordinate system. We present a concept for transferring multi-sensor data into a commonly referenced world coordinate system: the earth's magnetic field. The steady presence of our planetary magnetic field provides a reliable world coordinate system, which can serve as a reference for a position-defined reconstruction of dynamic environments. Our approach is evaluated using magnetic field sensors of the ZED 2 stereo camera from Stereolabs, which provides orientation relative to the North Pole similar to a compass. With the help of inertial measurement unit informations, each camera's position data can be transferred into the unified world coordinate system. Our evaluation reveals the level of quality possible using the earth magnetic field and allows a basis for dynamic and real-time-based applications of optical multi-sensors for environment detection.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 2 of its 23 references that are in the map. First posted on arXiv 12 Aug 2022.

Builds on

2 of 23 references.

References · 2

  1. 2019Visual-Inertial Navigation: A Concise Reviewcited by 28
  2. 2017Using Inertial Sensors for Position and Orientation Estimationcited by 18

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