在内陆河流中无人驾驶地面车辆的混合路径规划,基于避免碰撞的规定
Pengcheng Gao1, Pengfei Xu1, Hongxia Cheng1
1College of Harbor, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China.
Sensors (Basel, Switzerland)
|October 14, 2023
概括
本研究介绍了一种混合路径规划方法,用于在内陆河流中无人驾驶的地面车辆. 该方法通过结合改进的A*和模型预测控制算法来提高自主导航的安全性和效率.
科学领域:
- 机器人技术和自主系统
- 海军建筑和海洋工程.
- 智能运输系统 智能运输系统
背景情况:
- 在内陆水道,特别是长江,越来越多地使用无人驾驶地表车辆 (USV).
- 需要强大的自主导航系统来处理复杂的河流环境.
- 智能水路系统的进步需要复杂的路径规划.
研究的目的:
- 建议在内陆河流中为"Jinghai-I"USV提供混合路径规划方法.
- 加强全球路径优化和地方路径规划,以避免碰撞.
- 提高在复杂的河流条件下自主导航的准确性和安全性.
主要方法:
- 改进了A*算法,改进了启发式函数,并增加了约束 (通道边界,课程).
- 路径平滑,以符合内陆河流碰撞避免法规.
- 改进的模型预测控制 (MPC) 结合了路径偏差成本,拐角约束和特定场景的避免碰撞参数.
主要成果:
- 通过MPC调整成功降低了路径跟踪错误.
- 通过考虑导航规则和碰撞场景,提高了当地路线规划的合理性.
- 通过模拟实验来证明其有效性,模仿真实世界的导航条件.
结论:
- 混合路径规划方法有效地解决了内陆河流中USV导航的挑战.
- 完善的A*和MPC的集成为自主导航提供了一个强大的解决方案.
- 拟议的方法提高了安全性,效率和遵守航行法规.
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