Sparse Depth Enhanced Direct Thermal-Infrared SLAM Beyond the Visible Spectrum | IEEE Journals & Magazine | IEEE Xplore

Sparse Depth Enhanced Direct Thermal-Infrared SLAM Beyond the Visible Spectrum


Abstract:

In this letter, we propose a thermal-infrared simultaneous localization and mapping (SLAM) system enhanced by sparse depth measurements from light detection ranging (LiDA...Show More

Abstract:

In this letter, we propose a thermal-infrared simultaneous localization and mapping (SLAM) system enhanced by sparse depth measurements from light detection ranging (LiDAR). Thermal-infrared cameras are relatively robust against fog, smoke, and dynamic lighting conditions compared to RGB cameras operating under the visible spectrum. Exploiting thermal-infrared cameras for motion estimation and mapping is highly appealing. However, utilizing a thermal-infrared camera directly in existing vision-based methods is difficult because of the modality difference. This letter proposes a method to use sparse depth measurement for 6-DOF motion estimation via direct tracking under 14-bit raw measurement from the thermal camera. We also refine the local accuracy and include a loop closure to maintain global consistency. The experimental results demonstrate that the system is not only robust under various lighting conditions such as day and night, but it also overcomes the scale problem of monocular cameras.
Published in: IEEE Robotics and Automation Letters ( Volume: 4, Issue: 3, July 2019)
Page(s): 2918 - 2925
Date of Publication: 17 June 2019

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I. Introduction

Ego-motion estimation and mapping are crucial for an autonomous vehicle. Much of robotics research has focused on imaging sensors and LiDAR [1]–[5] for navigating environments without a global positioning system (GPS). Conventional RGB cameras operating under the human visible spectrum hinder in a challenging environment such as fog, dust, and complete darkness. Recently, thermal-infrared cameras have been highlighted by studies for their perceptual capability beyond the visible spectrum and their robustness regarding environmental changes.

References

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