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Sensor fusion of robotic total station and inertial navigation system for 6DoF tracking applications

Tomas Thalmann, Hans Neuner

Year
2024
Citations
4
Access
Open access

Abstract

Abstract This paper presents a novel approach for sensor fusion of robotic total station (RTS) and inertial navigation system (INS) to enable 6-degree-of-freedom (6DoF) pose estimation. Tight coupling of a spherical measurement model for RTS is developed, providing advantages over the traditional cartesian 3D-position measurement model, including supporting INS solution when distance measurements are unavailable and performing outlier detection in spherical observation space. Simulation studies demonstrate that replacing Global Navigation Satellite Systems (GNSS) with RTS for fusion with INS is beneficial in any environment (given line-of-sight (LOS) availability), even under ideal GNSS conditions. Furthermore, investigations on measurement models and failure identification over the entire range of RTS measurements reveal that the spherical model is advantageous over the cartesian model in certain regions. The developed methods are validated in a practical application for tilt compensation of an RTS pole, indicating a base 2D-RMSE of 3.8 mm for almost static and almost vertical poles, increasing with tilt and velocity.

Keywords

Computer scienceInertial navigation systemTracking (education)Computer visionInertial measurement unitArtificial intelligenceSensor fusionInertial frame of referenceFusionGeography

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