부산대학교 도서관

Highlights •Introduces a tightly coupled multi-sensor SLAM framework that harnesses the synergies of LiDAR, Camera, IMU, and GNSS.•Laser–visual–inertial odometry fusion system optimizes pose estimation, overcoming limitations of standalone methods.•Visual–laser fusion and GNSS factors improve loop closure efficiency, contributing to precise global pose estimation.•Refines laser–visual–inertial odometry, visual–inertial odometry, IMU preintegration, loop closure, and GNSS factors.•The proposed methodology excels in outdoor scenarios, elevating precision and resilience of SLAM algorithms for mobile robots.