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A Method for Constructing Software and Hardware of a Multi-Source Fusion Intelligent Driving Southeast University
- Format:
- Book
- Conference/Event
- Author/Creator:
- Zhan, Kaidi, author.
- Conference Name:
- 2024 International Conference on Smart Transportation Interdisciplinary Studies (2024-12-13 : Nanjing, China)
- Language:
- English
- Physical Description:
- 1 online resource cm
- Place of Publication:
- Warrendale, PA SAE International 2025
- Summary:
- To meet the requirements of high-precision and stable positioning for autonomous driving vehicles in complex urban environments, this paper designs and develops a multi-sensor fusion intelligent driving hardware and software system based on BDS, IMU, and LiDAR. This system aims to fill the current gap in hardware platform construction and practical verification within multi-sensor fusion technology. Although multi-sensor fusion positioning algorithms have made significant progress in recent years, their application and validation on real hardware platforms remain limited. To address this issue, the system integrates BDS dual antennas, IMU, and LiDAR sensors, enhancing signal reception stability through an optimized layout design and improving hardware structure to accommodate real-time data acquisition and processing in complex environments. The system's software design is based on factor graph optimization algorithms, which use the global positioning data provided by BDS to constrain the drift of IMU and LiDAR data, ensuring that the system can maintain accurate positioning through IMU and LiDAR collaboration, even when GNSS signals are limited or completely unavailable. Experimental results show that the system's 3D positioning error in shaded environments is controlled within 7 cm, with a convergence time of no more than 40 seconds. Further statistical analysis reveals a root mean square error (RMSE) of approximately 8 cm and a standard deviation (STD) of 2 cm. During the simulated indoor-outdoor scene transition test, the system's relative pose error remains stable within 10 cm, demonstrating its adaptability and robustness in diverse and complex scenarios. This study provides a technical reference for the hardware construction and system validation of multi-sensor fusion technology on autonomous driving platforms
- Notes:
- Vendor supplied data
- Publisher Number:
- 2025-01-7158
- Access Restriction:
- Restricted for use by site license
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