通过协作神经动力学优化来规划和形成自动地表车辆的自动地表车辆的安全关键的回落地平线规划和控制
IEEE transactions on cybernetics
|November 5, 2024
概括
本研究介绍了自动水面车辆 (ASV) 的新型三级控制系统,以确保安全导航和形成控制,即使存在不确定性和障碍. 该方法增强了ASV的安全关键规划和形成控制.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统 控制系统
- 自主导航自主导航自主导航自主导航自主导航自主导航
背景情况:
- 自主地表车辆 (ASV) 需要强大的控制,以便在复杂的环境中安全运行.
- 现有的方法经常与模型不确定性,环境干扰和避免障碍同时扎.
- 协调控制和路径规划对于多ASV系统至关重要.
研究的目的:
- 为ASVs制定一个安全关键的退缩地平线规划和形成控制战略.
- 应对模型不确定性,环境干扰和各种障碍所带来的挑战.
- 为加强ASV协调提出一个层次控制架构.
主要方法:
- 一个三层次的阵列控制架构:安全关键阵列轨迹生成,无碰撞引导和反干扰控制.
- 协作神经动力学优化,用于回落地平线轨迹规划和避开静止障碍物.
- 控制屏障功能用于视线指导,以避免移动的障碍物和其他车辆.
- 对于反干扰控制法而言,有限时间的收观察者.
主要成果:
- 拟议的方法有效地计划了ASV的安全形成轨迹,以回退的地平线的方式.
- 无碰撞引导确保避免移动的障碍物和其他车辆.
- 反干扰控制法使ASV能够准确地遵循指导命令.
- 模拟和硬件在循环中的实验验证了系统的有效性.
结论:
- 开发的三级控制架构显著改善了ASV的安全关键规划和形成控制.
- 该方法对模型不确定性和环境干扰具有稳定性.
- 这项工作为先进的ASV协调和导航提供了经过验证的框架.
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