自主海底覆盖与受限输入自主水下车辆:综合路径规划和控制
Athanasios K Gkesoulis1,2, Panagiotis Georgakis1,2, George C Karras2,3
1Department of Electrical and Computer Engineering, University of Patras, 26504 Patras, Greece.
Sensors (Basel, Switzerland)
|February 26, 2025
概括
本研究提出了一个自主水下车辆 (AUV) 的综合框架,以实现高效的海底覆盖. 该系统结合了最佳路径规划和可靠的水下操作的强大控制,包括碎片检测.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 海洋工程 海洋工程
- 控制系统 控制系统
背景情况:
- 自主水下车辆 (AUV) 需要复杂的路径规划和控制,以便在具有挑战性的环境中有效覆盖海底.
- 现实世界的运营面临障碍,干扰和物理限制,需要综合解决方案.
研究的目的:
- 为AUV开发和验证一个完全集成的框架,将最佳覆盖路径规划与强大的受约束控制相结合.
- 通过改进的导航和控制,增强AUV能力,用于诸如水下碎片检测等任务.
主要方法:
- 实施了最佳覆盖路径规划算法,使用先验区域信息来实现最大覆盖,最小转和避开障碍.
- 采用参考修改技术,在输入约束下进行可靠的途径点跟踪.
- 在 BlueROV2 平台上使用 ROS,Gazebo 和 ArduSub Software-in-the-Loop (SITL) 验证了集成框架.
主要成果:
- 在综合框架内证明了路径规划和控制策略之间的协同效应.
- 通过高准确度模拟验证了框架的有效性和准备能力,以便通过高准确度模拟对实际的海底作战进行准备.
结论:
- 综合路径规划和控制框架显著提高了AUV在海底覆盖任务的性能.
- 开发的系统是强大的,适合于现实世界的应用,如水下碎片检测.
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