Traceable Virtual Sea Trials in the Marine Robotics Unity Simulator for Manoeuvring Assessment of Unmanned Surface Vehicles
作者: Paria Rezayan
分类: cs.RO, eess.SY
发布日期: 2026-06-10
💡 一句话要点
提出标准化虚拟海试框架以提升无人水面艇操控评估
🎯 匹配领域: 支柱五:交互与反应 (Interaction & Reaction)
关键词: 无人水面艇 虚拟海试 水动力导数 系统识别 数字双胞胎 操控评估 模拟器
📋 核心要点
- 现有的物理海试方法在成本和安全性上存在限制,导致高保真操控数据难以获取。
- 论文提出了一个标准化的虚拟海试框架,自动化执行TC/ZZ操控并生成相关数据。
- 实验结果显示,TC测试的正常推进差异约为3.9%,ZZ测试的超调量保持在1度以内,符合IMO标准。
📝 摘要(中文)
准确识别水动力导数对于无人水面艇(USVs)的控制和导航至关重要,但物理海试的高保真操控数据受到成本和安全的限制。本文扩展了海洋机器人Unity模拟器(MARUS),引入了标准化的虚拟海试框架,实现了TC/ZZ操控的自动执行和数据生成,具备可追溯的指令-执行日志、系统识别(SI)数据处理和IMO/ITTC对齐的操控指标自动提取。关键贡献在于专门的TC/ZZ数据采集和后处理管道,提升了模拟器操控的重复性和可审计性,同时生成了适用于水动力导数识别和数字双胞胎工作流的SI准备数据集。案例研究结果表明,操控行为具有重复性和合规性。
🔬 方法详解
问题定义:本文旨在解决无人水面艇操控评估中高保真数据获取的困难,现有物理海试方法在成本和安全性上存在显著限制。
核心思路:通过扩展MARUS模拟器,构建一个标准化的虚拟海试框架,实现TC/ZZ操控的自动化执行和数据生成,以提高数据的可重复性和审计性。
技术框架:该框架包括指令-执行日志记录、数据处理模块和操控指标提取模块,形成一个完整的虚拟海试工作流。
关键创新:引入了专门的TC/ZZ数据采集和后处理管道,显著提升了模拟器操控的重复性和可审计性,生成SI准备数据集,支持水动力导数识别。
关键设计:在差动推力转向中,输入记录为有序的舵等效指令,实际执行记录为基于施加推力的执行级别代理,确保指令与执行的明确分离。
🖼️ 关键图片
📊 实验亮点
实验结果表明,TC测试中正常推进的差异约为3.9%,战术直径差异在4.6%至4.7%之间;ZZ测试中,超调量保持在1度以内,符合IMO标准,峰值偏航率在4.1至5.8度/秒之间,展示了框架的有效性和可靠性。
🎯 应用场景
该研究的虚拟海试框架可广泛应用于无人水面艇的操控评估、系统识别和数字双胞胎的校准,具有重要的实际价值。未来,该框架可能推动无人水面艇在复杂环境中的自主导航和操控能力的提升。
📄 摘要(原文)
Accurate identification of hydrodynamic derivatives is essential for control and navigation of Unmanned Surface Vehicles (USVs), but high-fidelity manoeuvring data from physical sea trials are constrained by cost and safety. Turning Circle (TC) and Zig-Zag (ZZ) trials remain fundamental to IMO and ITTC assessment procedures. This paper extends the Marine Robotics Unity Simulator (MARUS) by introducing a standardised Virtual Sea Trial framework for automated execution and data generation of TC/ZZ manoeuvres, with traceable command-actuation logging, system-identification (SI)-focused data conditioning, and automated extraction of IMO/ITTC-aligned manoeuvring metrics. A key contribution is a dedicated TC/ZZ data acquisition and post-processing pipeline, improving the repeatability and auditability of simulator-based manoeuvres while producing SI-ready datasets for hydrodynamic-derivative identification and digital-twin workflows. Another feature is explicit command-execution separation for differential-thrust steering, where inputs are recorded as ordered rudder-equivalent commands and realised actuation is logged as an execution-level proxy derived from applied thrust. Case-study results demonstrate repeatable and compliant manoeuvre behaviour. For TC tests, the normalised advance differs by approximately 3.9 percent between port and starboard sides, while the tactical diameter differs by approximately 4.6 to 4.7 percent. For ZZ tests, first and second overshoot excesses remain below 1 degree for both +/- 10 degree and +/- 20 degree manoeuvres, satisfying IMO criteria, while peak yaw rates range from approximately 4.1 to 5.8 deg/s. Overall, the framework provides a repeatable and auditable virtual sea-trial workflow for generating IMO/ITTC-aligned datasets and supporting system identification, hydrodynamic-derivative estimation, and digital-twin calibration.