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Updated: Feb 14, 2026

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适应性多摄像头融合和校准用于大规模多车辆合作模拟场景
Hui Zhang1, Chenyu Xia1, Huantao Zeng2
1School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518107, China.
Sensors (Basel, Switzerland)
|February 13, 2026
概括
本研究介绍了用于协作硬件在循环 (HIL) 模拟的多摄像头视觉系统. 该方法增强了实时感知和准确的车辆位置估计,以实现高效的合作控制.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 计算机视觉 计算机视觉
- 机器学习 机器学习
背景情况:
- 准确的车辆姿势估计对于多车辆合作硬件在循环 (HIL) 仿真平台至关重要.
- 单眼视觉系统面临视野和分辨率在实时多目标感知方面的局限性.
研究的目的:
- 提出一个以工程为导向的多摄像头合作视觉检测方法.
- 为了提高HIL模拟中的处理效率,实时性能和检测精度.
主要方法:
- 将多摄像头成像结果投射到一个统一的物理平面上.
- 预先计算和缓存图像拼接参数,以实现快速并行图像马赛克.
主要成果:
- 实现了93.41%的识别码识别率和99.08%的识别准确度.
- 用高分辨率输入 (1440 × 960) 生成每秒30的拼接图像流.
结论:
- 拟议的方法满足了对工程应用的检测精度和实时处理的双重要求.
- 这种方法显著提高了合作HIL模拟的感知能力.
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