基于BDS和视觉视觉的平板卡车的高精度定位和旋转角度估计
Xinli Yu1, Yufei Ren1, Xiaoxv Yin1
1Qilu Aerospace Information Research Institute, Jinan 250100, China.
Sensors (Basel, Switzerland)
|March 28, 2024
概括
本研究提出了一种新方法,用于精确的平板卡车定位和旋转角度估计,使用北斗导航卫星系统 (BDS) 和视觉技术,这对于自动化叉车加载至关重要.
科学领域:
- 机器人和自动化机器人与自动化
- 地理空间导航的导航
- 计算机视觉 计算机视觉
背景情况:
- 无人叉车的自动装载系统需要厘米级的精度来定位平板卡车和估计旋转角度.
- 现有的方法在动态工业环境中实现必要的准确性方面面临挑战.
研究的目的:
- 开发和验证平板卡车的高精度定位和旋转角度估计方法.
- 为了提高无人叉车自动装载操作的效率和安全性.
主要方法:
- 在无人叉车上使用了北斗卫星导航系统 (BDS) 和飞行时间 (ToF) 摄像头.
- 使用深度双分辨率网络-23-slim (DDRNet-23-slim) 进行平底细分和Hough转换用于边缘线提取.
- 开发了一个邻近特征向量,用于端点识别和BDS定位,用于坐标转换.
主要成果:
- 取得的终点定位误差低于3厘米.
- 获得的旋转角度估计误差小于0.3度.
- 通过实验验证证明了拟议方法的有效性和可靠性.
结论:
- 综合的BDS和基于视觉的方法有效地解决了精确的平板卡车定位和旋转估计的挑战.
- 该方法为改善无人叉车系统的自动装载操作提供了可靠的解决方案.
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