A Theoretical Framework for High-Precision and Simultaneous Localization and Mapping Through Multi-Sensor Fusion

Yizhe Chen

doi:10.6919/ICJE.202607_12(7).0003

Authors

Yizhe Chen Shanghai Experimental Foreign Language School, Shanghai 200093, China

DOI:

https://doi.org/10.6919/ICJE.202607_12(7).0003

Keywords:

SLAM; Multi-Sensor Fusion; Graph Optimization; State Estimation; Robust Perception; Sensor Calibration; UAV., ccccccccccc

Abstract

Simultaneous Localization and Mapping (SLAM) always contains a core challenge for autonomous systems, that is, single-sensor architectures are often not enough in complex real-world environments. We propose a theoretical framework that combines stereo vision, LiDAR, IMU, and GPS, achieving high precision and robustness by adding their complementary strengths. The framework systematically addresses sensor fusion, state estimation, loop closure, and map representation, and also lays out a perfect experimental blueprint. The challenging aim is to orient SLAM research toward practical autonomy, with a focus on robustness, accuracy, and computational efficiency.

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