基于视觉的定位在城市地区移动机器人的机器人.
Erdal Alimovski1, Gokhan Erdemir2, Ahmet Emin Kuzucuoglu3
1Computer Engineering Department, Istanbul Sabahattin Zaim University, 34303 Istanbul, Türkiye.
Sensors (Basel, Switzerland)
|February 26, 2025
概括
本研究介绍了城市户外机器人的视觉定位系统,在信号问题地区的GPS性能优于GPS. 该系统使用文本识别来实现精确的机器人定位,以最小的错误.
科学领域:
- 机器人和计算机视觉 机器人和计算机视觉
- 自主导航系统 自主导航系统
- 地理空间定位技术
背景情况:
- 强大的自主导航依赖于准确的定位,这是移动机器人的关键因素.
- 全球定位系统 (GPS) 是户外定位的标准,但在城市环境中由于障碍物而遭受信号退化.
- 这种局限性需要替代本地化方法,以便在具有挑战性的城市环境中可靠运行.
研究的目的:
- 为在拥挤的城市环境中运行的户外移动机器人提出和评估基于视觉的定位系统.
- 解决GPS在信号阻塞或精度降低的地区的局限性.
- 为了提高移动机器人定位的准确性和可靠性,使用易于获得的视觉数据.
主要方法:
- 利用高效准确的场景文本检测器 (EAST) 算法进行城市文本检测.
- 采用EasyOCR进行文本识别,随后采用后处理和文字相似算法来完善提取的信息.
- 与Places API集成识别的文本数据以获取地理坐标和并行收集的 POI 数据.
主要成果:
- 拟议的视觉定位系统在各种城市场景中显示出约4米的低定位误差.
- 该系统在不同的照明条件 (早晨,晚上) 和三个不同的城市测试区域中被证明是有效的.
- 性能评估显示,与使用单个传感器的现有方法相比,性能始终优于现有方法.
结论:
- 开发的基于视觉的系统为移动机器人定位在无GPS或退化城市环境中提供了可行和有效的解决方案.
- 该方法成功地利用场景文本识别和外部API来实现准确的地理空间定位.
- 这项研究强调了基于视觉的技术在复杂的现实应用中克服传统本地化方法的局限性的潜力.
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