Closed-Form 6-DoF Pose Estimation of Medical Tools via Gradiometer-Based Electromagnetic Localization System
Overview
This research introduces a Gradiometer-Based Electromagnetic Localization System (GELS) that enables closed-form six-degree-of-freedom pose estimation for medical tools without requiring pre-calibrated workspace field maps or iterative optimization. By utilizing a compact magnetometer array as an embedded quasi-gradiometer, the system estimates local magnetic fields and gradient tensors to recover array orientation and position through Procrustes registration over multiple sources. Benchtop experiments across various sensor configurations demonstrate a median solver runtime of 172 microseconds, with perturbation analysis highlighting inter-sensor inconsistency and dipole model mismatch as key factors affecting accuracy.
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Reported quantity · solver runtime: 172 other · Basis not reported
“on pipeline, with a median solver runtime of \SI{172.00}{\micro\second}. A perturbation analysis identifies inter-sensor inconsistency and dipole model mismatch as dominant accuracy limits, informing future sensor array and source design to improve pose accuracy.”
Exact source · revision 1Source owner not reported
Reported quantity · runtime: 172 other · Basis not reported
“on pipeline, with a median solver runtime of \SI{172.00}{\micro\second}. A perturbation analysis identifies inter-sensor inconsistency and dipole model mismatch as dominant accuracy limits, informing future sensor array and source design to improve pose accuracy.”
Exact source · revision 1Source owner not reported
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- arXiv Robotics — research abstractsSignalClosed-Form 6-DoF Pose Estimation of Medical Tools via Gradiometer-Based Electromagnetic Localization System
This research introduces a Gradiometer-Based Electromagnetic Localization System (GELS) that enables closed-form six-degree-of-freedom pose estimation for medical tools without requiring pre-calibrated workspace field maps or iterative optimization. By utilizing a compact magnetometer array as an embedded quasi-gradiometer, the system estimates local magnetic fields and gradient tensors to recover array orientation and position through Procrustes registration over multiple sources. Benchtop experiments across various sensor configurations demonstrate a median solver runtime of 172 microseconds, with perturbation analysis highlighting inter-sensor inconsistency and dipole model mismatch as key factors affecting accuracy.
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