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蒋子捷(博士生)、蔡忠亮的论文在SENSORS刊出
发布时间:2023-12-21 13:14:47     发布者:易真     浏览次数:

标题:Multi-Level Optimization for Data-Driven Camera-LiDAR Calibration in Data Collection Vehicles

Author(s): Jiang, ZJ (Jiang, Zijie); Cai, ZL (Cai, Zhongliang); Hui, N (Hui, Nian); Li, BZ (Li, Bozhao)

Source: SENSORS  Volume: 23  Issue: 21  Article Number: 8889  DOI: 10.3390/s23218889  Published: NOV 2023  

摘要: Accurately calibrating camera-LiDAR systems is crucial for achieving effective data fusion, particularly in data collection vehicles. Data-driven calibration methods have gained prominence over target-based methods due to their superior adaptability to diverse environments. However, current data-driven calibration methods are susceptible to suboptimal initialization parameters, which can significantly impact the accuracy and efficiency of the calibration process. In response to these challenges, this paper proposes a novel general model for the camera-LiDAR calibration that abstracts away the technical details in existing methods, introduces an improved objective function that effectively mitigates the issue of suboptimal parameter initialization, and develops a multi-level parameter optimization algorithm that strikes a balance between accuracy and efficiency during iterative optimization. The experimental results demonstrate that the proposed method effectively mitigates the effects of suboptimal initial calibration parameters, achieving highly accurate and efficient calibration results. The suggested technique exhibits versatility and adaptability to accommodate various sensor configurations, making it a notable advancement in the field of camera-LiDAR calibration, with potential applications in diverse fields including autonomous driving, robotics, and computer vision.

作者关键词: camera-LiDAR calibration; automatic calibration; targetless registration; data fusion; autonomous driving

地址: [Jiang, Zijie; Cai, Zhongliang; Hui, Nian; Li, Bozhao] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

通讯地址: Cai, ZL (corresponding author), Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

邮箱地址: jiangzijie@whu.edu.cn; zlcai@whu.edu.cn; huinian@whu.edu.cn; libozhao@whu.edu.cn

影响因子:3.9


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