道路网络地图辅助的车辆定位基于姿势图的优化
Shuchen Xu1, Yongrong Sun1, Kedong Zhao1
1National Key Laboratory of Helicopter Aeromechanics, College of Automation Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing 211106, China.
Sensors (Basel, Switzerland)
|September 9, 2023
概括
本研究引入了一种新方法,通过将视觉公里测量与道路网络地图相结合,提高城市地区的车辆定位准确性. 该方法纠正累积的错误,增强实时位置估计.
科学领域:
- 机器人技术和自主系统
- 计算机视觉 计算机视觉
- 地理信息系统 地理信息系统
背景情况:
- 由于信号阻塞,卫星导航系统在城市环境中难以准确.
- 视觉测距提供了一个替代方案,但它遭受了死算中固有的累积定位错误.
研究的目的:
- 开发一种强大的车辆定位方法,克服在城市环境中视觉测距的局限性.
- 通过整合道路网络地图信息,提高实时车辆定位的准确性和稳定性.
主要方法:
- 一种新的道路网络地图辅助定位方法,利用姿势图优化理论.
- 整合视觉测距计时计时输出与从点线形式的道路网络地图中获得的约束.
- 开发一个优化和预测模型,使用地图校正点来纠正视觉测距轨迹.
主要成果:
- 拟议的方法有效地抑制了视觉测距的累积定位错误.
- 在KITTI和校园数据集上的实验结果显示,与类似的地图辅助技术相比,性能优越.
- 该方法实现了稳定和准确的实时车辆位置估计.
结论:
- 道路网络地图辅助的视觉测距显著提高了在具有挑战性的城市环境中车辆定位的准确性.
- 姿势图优化方法为纠正死亡计算漂移提供了一个可靠的框架.
- 这种方法为精确可靠的自动驾驶车辆导航提供了一个有希望的解决方案.
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