# Keyframe-based Direct Thermal-Inertial Odometry

## TL;DR

This paper introduces a novel thermal-inertial odometry method that fuses thermal camera data with inertial measurements to enable reliable navigation in GPS-denied and visually degraded environments, including darkness and obscurants.

## Contribution

It presents an optimization-based fusion approach for thermal and inertial data, extending robotic navigation capabilities in challenging conditions.

## Key findings

- Successfully verified in indoor laboratory tests with ground-truth.
- Demonstrated robustness in underground mine with severe visual degradation.
- Achieved accurate localization in GPS-denied, dark, and obscurant-filled environments.

## Abstract

This paper proposes an approach for fusing direct radiometric data from a thermal camera with inertial measurements to extend the robotic capabilities of aerial robots for navigation in GPS-denied and visually degraded environments in the conditions of darkness and in the presence of airborne obscurants such as dust, fog and smoke. An optimization based approach is developed that jointly minimizes the re-projection error of 3D landmarks and inertial measurement errors. The developed solution is extensively verified against both ground-truth in an indoor laboratory setting, as well as inside an underground mine under severely visually degraded conditions.