在局部不确定性的情况下,为最佳导航提供一个框架
Charifou Orou Mousse1, Mohamed Benrabah1, François Marmoiton1
1Université Clermont Auvergne, Centre National de Recherche Scientifique, Clermont Auvergne INP, Institut Pascal UMR6602, F-63000 Clermont-Ferrand, France.
Sensors (Basel, Switzerland)
|August 26, 2023
概括
本研究为自动驾驶汽车提供了一个新的框架,用于独立管理路径跟踪和避开障碍物,即使局部不确定性. 这样可以确保更安全的航行,防止位置错误影响障碍物检测和避开机动.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 自主系统 自主系统
- 导航 导航 导航 导航 导航
背景情况:
- 自动驾驶汽车依赖于遵循路径和避开障碍物来进行导航.
- 定位不确定性对这些功能产生重大影响,往往需要完全停止以确保安全.
- 现有的方法在不确定的本地化条件下努力保持性能.
研究的目的:
- 开发一个框架,最好地结合路径遵循和避开障碍.
- 为了确保这两个关键的功能保持独立,尽管本地化不确定性.
- 为了使移动机器人能够进行强大的导航,即使位置不准确.
主要方法:
- 提出了自动驾驶汽车导航的新框架.
- 实现了独立的路径跟踪和避障模块.
- 在PAVIN实验平台上在EZ10航天飞机上测试了框架.
主要成果:
- 拟议的框架成功地结合了路径遵循和避开障碍.
- 定位不确定性只影响了路径遵循,而不是避开障碍物.
- 在机器人的局部参考框架中,避免障碍物是有效的,独立于绝对位置准确性.
结论:
- 开发的方法可以确保移动机器人的无碰撞导航.
- 对于在不准确的本地化下运行的自主系统来说,这是一个有前途的解决方案.
- 避难障碍与定位不确定性的独立性提高了航行安全性和可靠性.
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