多传感器辅助的低成本室内非视觉语义地图构建和定位,用于现代汽车
Guangxiao Shao1, Fanyu Lin2, Chao Li3
1College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266061, China.
Sensors (Basel, Switzerland)
|July 13, 2024
概括
本研究介绍了使用非视觉语义映射和定位的现代车辆的低成本室内定位系统. 它在检测地标和低定位误差方面实现了高精度,增强了车辆导航.
科学领域:
- 汽车工程 汽车工程
- 机器人技术和自主系统
- 地理空间信息科学 地理空间信息科学
背景情况:
- 汽车行业的发展需要为互联和自动驾驶汽车提供先进的定位.
- 现有的室内定位方法往往缺乏成本效益或无集成,用于各种车辆系统.
- 智能汽车系统 (信息娱乐,汽车互联网,自动驾驶) 需要强大的室内/室外定位.
研究的目的:
- 为现代车辆提供低成本,多功能室内非视觉语义映射和本地化解决方案.
- 开发一种在没有视觉输入的情况下识别非视觉语义地标的方法.
- 创建一个精确的本地化系统,利用语义地图特征和传感器数据.
主要方法:
- 基于移动窗口的语义地标检测,用于入口和道路节点等功能.
- 构建一个室内语义地图,整合车辆轨迹,地标和Wi-Fi RSS指纹.
- 使用地标匹配和利用地标相关性进行图形优化本地化.
主要成果:
- 在非视觉语义地标检测中,准确度高达98.1%.
- 在实地实验中实现了1.31米的低定位误差.
- 在各种地下停车场环境中成功验证.
结论:
- 拟议的方法为室内车辆定位提供了一种具有成本效益和多功能性的解决方案.
- 非视觉语义映射和基于地标的定位增强了复杂的室内环境中的导航准确性.
- 这种方法支持将先进的智能系统集成到现代汽车中.
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