基于回归的对接系统,用于使用单眼相机和ArUco标记器的自主移动机器人
Jun Seok Oh1, Min Young Kim2,3,4
1School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Republic of Korea.
Sensors (Basel, Switzerland)
|June 27, 2025
概括
本研究介绍了一种低成本的自主充电系统,使用单眼相机和ArUco标记器. 新的基于回归的方法准确地估计了距离和方向,超过了工业应用的传统视觉技术.
科学领域:
- 机器人和自动化 机器人和自动化
- 计算机视觉 计算机视觉
- 人工智能的人工智能
背景情况:
- 传统的单眼视觉系统由于对视角,照明和校准的敏感性而难以准确地进行空间估计.
- 像SolvePnP这样的现有方法在距离和方向估计中表现出严重的错误.
研究的目的:
- 开发一个具有成本效益的自主充电对接系统,使用单眼相机和ArUco标记器.
- 通过克服传统方法的局限性,提高自主对接空间估计的准确性.
主要方法:
- 提出了一种基于回归的新方法,从ArUco标记器变化 (大小,形状) 中学习几何特征,用于距离和方向估计.
- 该模型使用来自LiDAR传感器的地面真实数据进行训练.
- 实时操作仅依赖于单眼相机输入.
主要成果:
- 拟议系统的平均距离误差为1.18厘米,平均方向误差为3.11°.
- 这显著优于SolvePnP,其误差为58.54厘米和6.64°.
- 现实世界对接测试显示,平均位置误差为2厘米,定向误差为3.07°.
结论:
- 精确可靠的自主对接可以通过低成本,仅视觉硬件实现.
- 开发的系统为工业自主充电应用提供了实用且可扩展的解决方案.
- 基于回归的方法有效地解决了传统单眼视觉技术的局限性.
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