Dynamic Sensor Matching based on Geomagnetic Inertial Navigation

TL;DR

This paper introduces a method for aligning multi-sensor data in dynamic environments by using Earth's magnetic field as a common reference, enabling real-time environment reconstruction.

Contribution

The paper proposes a novel approach to transfer multi-sensor data into a unified coordinate system based on Earth's magnetic field, enhancing dynamic environment sensing.

Findings

Magnetic field sensors enable reliable sensor data alignment.

Inertial data improves position transfer accuracy.

The approach supports real-time environment detection.

Abstract

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.