Trust Your IMU: Consequences of Ignoring the IMU Drift
- URL: http://arxiv.org/abs/2103.08286v2
- Date: Tue, 16 Mar 2021 20:25:39 GMT
- Title: Trust Your IMU: Consequences of Ignoring the IMU Drift
- Authors: Marcus Valtonen \"Ornhag and Patrik Persson and M{\aa}rten Wadenb\"ack
and Kalle {\AA}str\"om and Anders Heyden
- Abstract summary: We develop the first-ever solver to jointly solve the relative pose problem with unknown and equal focal length and radial distortion profile.
We show significant speed-up compared to state-of-the-art algorithms, with small or negligible loss in accuracy for partially calibrated setups.
We evaluate the proposed solvers on different commercially available low-cost UAVs, and demonstrate that the novel assumption on IMU drift is feasible in real-life applications.
- Score: 2.253916533377465
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In this paper, we argue that modern pre-integration methods for inertial
measurement units (IMUs) are accurate enough to ignore the drift for short time
intervals. This allows us to consider a simplified camera model, which in turn
admits further intrinsic calibration. We develop the first-ever solver to
jointly solve the relative pose problem with unknown and equal focal length and
radial distortion profile while utilizing the IMU data. Furthermore, we show
significant speed-up compared to state-of-the-art algorithms, with small or
negligible loss in accuracy for partially calibrated setups. The proposed
algorithms are tested on both synthetic and real data, where the latter is
focused on navigation using unmanned aerial vehicles (UAVs). We evaluate the
proposed solvers on different commercially available low-cost UAVs, and
demonstrate that the novel assumption on IMU drift is feasible in real-life
applications. The extended intrinsic auto-calibration enables us to use
distorted input images, making tedious calibration processes obsolete, compared
to current state-of-the-art methods.
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