GICI-LIB: A GNSS/INS/Camera Integrated Navigation Library
Cheng Chi, Xin Zhang, Jiahui Liu, Yulong Sun, Zihao Zhang, and Xingqun, Zhan

TL;DR
This paper introduces GICI-LIB, an open-source library for GNSS/INS/camera integrated navigation, featuring a flexible factor graph framework that enhances multi-sensor fusion accuracy and robustness in diverse environments.
Contribution
The paper presents a comprehensive, flexible, and open-source GNSS/INS/camera integration library with a detailed dataset and a factor graph optimization framework for improved navigation accuracy.
Findings
GICI-LIB effectively combines multiple GNSS error sources for robust navigation.
The framework supports various algorithms like RTK and PPP with high accuracy.
Results demonstrate continuous precise navigation in urban environments.
Abstract
Accurate navigation is essential for autonomous robots and vehicles. In recent years, the integration of the Global Navigation Satellite System (GNSS), Inertial Navigation System (INS), and camera has garnered considerable attention due to its robustness and high accuracy in diverse environments. However, leveraging the full capacity of GNSS is cumbersome because of the diverse choices of formulations, error models, satellite constellations, signal frequencies, and service types, which lead to different precision, robustness, and usage dependencies. To clarify the capacity of GNSS algorithms and accelerate the development efficiency of employing GNSS in multi-sensor fusion algorithms, we open source the GNSS/INS/Camera Integration Library (GICI-LIB), together with detailed documentation and a comprehensive land vehicle dataset. A factor graph optimization-based multi-sensor fusion…
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Taxonomy
TopicsRobotics and Sensor-Based Localization · Inertial Sensor and Navigation · Maritime Navigation and Safety
