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边缘触发的三维物体检测使用LiDAR环
Eunji Song1, Seyoung Jeong1, Sung-Ho Hwang1
1Department of Mechanical Engineering, Sungkyunkwan University, 2066 Seobu-ro, Suwon 16419, Republic of Korea.
Sensors (Basel, Switzerland)
|March 28, 2024
概括
这项研究引入了一种更快,更准确的方法,用于使用LiDAR环数据进行自动驾驶物体识别. 这种新的方法在高速场景中提高了检测性能,超过了现有的方法.
科学领域:
- 机器人和人工智能 机器人和人工智能
- 计算机视觉 计算机视觉
- 传感器数据处理 传感器数据处理
背景情况:
- 高速自动驾驶需要快速准确地识别物体,包括小物体.
- 现有的方法在动态环境中实现速度和准确性方面面临挑战.
研究的目的:
- 开发一种高效的对象点提取方法,用于自动驾驶.
- 在高速情况下使用LiDAR数据提高对象识别的速度和性能.
主要方法:
- 使用基于规则的LiDAR环数据和边缘触发器用于对象点提取的新方法.
- 将LiDAR环信息解释为数字脉冲,以有效地去除地面点.
- 检测不连续的z值边缘与环ID和天线对齐,用于对象点识别.
- 使用 DBSCAN 和 PCA 来创建界限框和识别性能评估.
主要成果:
- 与RANSAC相比,拟议的方法在SemanticKITTI和Waymo开放数据集上表现出更高的F1分数,用于地面移除和点提取.
- 使用新方法的对象界限框提取实现了更高的PDR指数性能.
- 跨开放数据集,虚拟和现实驾驶环境的验证证实了该方法的有效性.
结论:
- 提出的基于LiDAR的对象点提取方法显著提高了自动驾驶识别的速度和性能.
- 这种技术提供了一个强大的解决方案,用于在高速驾驶条件下准确检测物体,即使是小物体.
- 该方法显示了在先进的驾驶辅助系统和完全自动驾驶汽车中实际实施的巨大潜力.
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