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基于ICP的地图和定位系统,用于使用2D LiDAR的AGV
Felype de L Silva1, Eisenhawer de M Fernandes1, Péricles R Barros1
1Laboratory of Electronic Instrumentation and Control (LIEC), Department of Electrical Engineering (DEE), Federal University of Campina Grande (UFCG), Campina Grande 58429-900, PB, Brazil.
Sensors (Basel, Switzerland)
|August 14, 2025
概括
这项研究开发了一种实时同步定位和绘图 (SLAM) 系统,用于仅使用2D LiDAR传感器的自动引导车辆 (AGV). 该系统实现了高姿势估计精度,为机器人应用程序提供了强大的导航和绘图.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 计算机视觉 计算机视觉
- 传感器融合式传感器
背景情况:
- 现有的SLAM系统通常需要多个传感器或大量的计算资源.
- 自动驾驶汽车 (AGV) 需要可靠的感知来实现自动驾驶.
- 对于嵌入式机器人平台来说,低复杂度,独立于传感器的解决方案至关重要.
研究的目的:
- 开发一个功能性,实时的SLAM系统用于AGV,仅使用2D LiDAR传感器.
- 创建一个低复杂度的系统,适应嵌入式平台,具有有限的计算能力.
- 解决当前文献中关于传感器独立性和资源效率的局限性.
主要方法:
- 使用代最接近点 (ICP) 算法集成扫描对齐.
- 使用高斯-牛顿优化和点对平面度量来估计姿势.
- 开发了一种轻量级的图形界面,用于实时可视化传感器数据,姿势和地图.
主要成果:
- 实现了高姿势估计准确度:99.42% (x),99.6% (y) 和99.99% (θ).
- 在受控环境中证明有效的本地化和渐进式环境映射.
- 系统的功能证明了机器人应用程序,尽管中等的更新率.
结论:
- 开发的SLAM系统为移动平台提供了强大而适应性的基础.
- 模块化架构支持未来的扩展,如轨迹规划和控制.
- 潜在的应用包括工业自动化,学术研究和机器人教育.
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