LOTUSim-Energy：自主海上运维中人与无人机交互的海事模拟器
LOTUSim-Energy: A Maritime Simulator for Human-Drone Interaction in Autonomous Offshore Operation \& Maintenance
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中文总结 AI 辅助
本文提出LOTUSim-Energy海事模拟器，统一异构无人航行器与环境物理，提供沉浸式监督界面，用于海上运维中人机交互的集成测试与演练，以降低实际部署风险。
中文摘要 AI 辅助
海上维护需要在空中、水面和水下领域进行操作，并包含人工监督。本文介绍了LOTUSim-Energy，一个专为海上运维中多领域人机交互设计的实时海事模拟器。该平台在分布式架构中统一了异构无人航行器（无人机：UAVs，无人水面艇：USVs，自主水下航行器：AUVs，遥控潜航器：ROVs），该架构耦合了环境作用力（风、浪、流），并提供沉浸式用户界面（桌面端和虚拟现实）用于监督。结构化的海上任务库使得在真实海洋气象扰动下对自主技术栈进行可重复评估成为可能。该模拟器支持真实物理、能量感知电池建模和故障检测流程，作为模块化验证工具。系统级性能在针对单桩和过渡段结构的多领域巡检场景中得到展示，我们在此评估了集成航点跟随插件和自动识别系统（AIS）参考轨迹跟踪在实时能量监控下的可靠性。通过结合统一的环境物理、异构航行器模拟和沉浸式监督，LOTUSim-Energy为原型设计和演练海上人机协作工作流提供了一个集成测试平台，作为降低海上部署风险的一步。
英文摘要
Offshore maintenance requires operations in the air, the surface, and the subsea domain and include human supervision. This paper presents LOTUSim-Energy, a real-time maritime simulator designed for multi-domain human--drone interaction for offshore operation and maintenance. The plat- form unifies heterogeneous unmanned vehicles (Unmanned Aerial Vehicles: UAVs, Unmanned Surface Vehicles: USVs, Autonomous Underwater Vehicles: AUVs, Remotely Operated Vehicles: ROVs) within a distributed architecture coupling environment forcing (wind, waves, currents) and provides immersive user interfaces for supervision (desktop and virtual reality). A structured offshore task library enables repeatable evaluation of autonomy stacks under realistic metocean disturbances. The simulator supports realistic physics, energy-aware battery modeling, and fault-detection pipelines as modular validation tools. System-level performance is demonstrated on a multi-domain inspection scenario for monopile and transition piece structure, where we evaluate the reliability of integrated waypoint-follower plugin and Automatic Identification System (AIS)-referenced trajectory tracking under real-time energy monitoring. By combining unified environmental physics, heterogeneous vehicle simulation, and immersive supervision, LOTUSim-Energy provides an integration testbed for prototyping and rehearsing offshore human--robot collaboration workflows, as a step toward de-risking sea deployment.
发表机构
- Naval Group（海军集团）
- CNRS（法国国家科学研究中心）
- IMT Atlantique（大西洋国立高等矿业电信学院）
机构由 AI 辅助整理，请以论文原文为准。
