Toshihiro Kitajima — accepted AI-conference papers

2025

Self-TIO: Thermal-Inertial Odometry via Self-Supervised 16-Bit Feature Extractor and Tracker

Junwoon Lee, Taisei Ando, Mitsuru Shinozaki, Toshihiro Kitajima, Qi An, Atsushi Yamashita

RA-L 2025

In recent years, thermal odometry has gained significant attention in mobile robotics for addressing visually degraded scenes. To achieve reasonable robustness and accuracy of thermal odometry, a learning-based image feature extractor and tracker has been proposed. While learning-based methods gener

Cited by 3 Source ↗Scholar ↗

2024

Switch-SLAM: Switching-Based LiDAR-Inertial-Visual SLAM for Degenerate Environments

Junwoon Lee, Ren Komatsu, Mitsuru Shinozaki, Toshihiro Kitajima, Hajime Asama, Qi An +1

RA-L 2024

This letter presents Switch-SLAM, switching-based LiDAR-inertial-visual SLAM for degenerate environments, designed to tackle the challenges in degenerate environments for LiDAR and visual SLAM. Switch-SLAM achieves high robustness and accuracy by utilizing a switching structure that transitions from

Cited by 44 Source ↗Scholar ↗