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一本小说 矢量化 曲线道路表示 基于空中导航 无人驾驶车辆轨迹规划
Sujie Zhang1, Qianru Hou2,3, Xiaoyang Zhang2,3
1Tianjin College, University of Science & Technology Beijing, Tianjin 301830, China.
Sensors (Basel, Switzerland)
|August 26, 2023
概括
本研究介绍了一种空地协作方法,用于通过复杂的地形引导无人驾驶地面车辆. 它提高了道路装配的准确性,并减少了有效导航的旅行时间.
科学领域:
- 机器人技术和自主系统
- 计算机视觉 计算机视觉
- 人工智能的人工智能
背景情况:
- 无人驾驶车辆因视野有限和路径提取不准确而难以在复杂的山地地形上导航.
- 使用无人机进行指导的传统方法只能提供像素级信息,从而损害了道路装配的准确性和车辆的速度.
研究的目的:
- 开发一种创新的空中-地面协作方法,用于矢量化曲线道路表示和轨迹规划.
- 提高无人地面车辆在具有挑战性的环境中导航的准确性和效率.
主要方法:
- 利用K-Means对道路明星点进行分类,以简化道路装配.
- 实现了一种 GA-Bézier 算法,用于道路矢量化和最佳框架识别.
- 沿着"路线平面"采用平滑的轨迹规划,以最大限度地提高转点的速度.
主要成果:
- 在道路装配效果 (EV) 中取得了显著的改进,并减少了模型运行时间 (T型).
- 通过在拐点上最大限度地提高速度,最大限度地减少旅行时间 (T-travel).
- 通过广泛的模拟和比较实验,证明了卓越的效率和准确性.
结论:
- 拟议的空地协作方法有效地解决了当前无人驾驶汽车导航系统的局限性.
- 这种方法提高了道路装配的准确性,减少了计算时间,并优化了复杂地形的行驶速度.
- 这种方法为在具有挑战性的,视觉复杂的环境中实现自主导航提供了强大的解决方案.
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