构建多无人艇协同感知仿真平台，生成真实感多模态数据。
MMUSV-Sim: A Perception-Oriented Simulation and Data-Generation Platform for Multi-USV Cooperative Perception
- 基于UE5与AirSim构建可配置的多艇仿真环境
- 生成多模态数据，协作检测精度提升至72.74 [email protected]
- 适合海洋智能感知、无人系统研发人员使用
多无人水面艇（USVs）间的协同感知通过融合互补观测，将海上目标探测范围扩展至单个平台视野之外。大规模系统开发亟需统一的工作流支持可配置的多艇场景、多模态采集和共享标注。我们提出MMUSV-Sim，一个基于Unreal Engine 5与Project AirSim的面向感知的海事仿真与数据生成平台。该平台提供岛屿、开阔海域和港口环境；支持可配置的天气、昼夜、波浪条件；包含丰富的舰船资产库；采用样条路径实现多艇运动控制。平台在多个USVs上同步采集RGB、深度、语义、LiDAR与雷达数据，并记录共享世界状态以导出每智能体的标注。实验验证了波浪设置对艇体垂荡、横摇、纵摇的有效调控，评估了投影标注与语义渲染间的几何一致性。在生成的多艇数据集上，基于LiDAR的协作BEV检测中，早期融合方法达到72.74的[email protected]，显著优于单艇的45.54。
原文摘要 · Abstract (English)
Cooperative perception among multiple unmanned surface vehicles (USVs) combines complementary observations to extend maritime target sensing beyond the view range and field of a single platform. Developing such systems at scale calls for a unified workflow for configurable multi-USV scenarios, multimodal acquisition, and shared annotations. We present MMUSV-Sim, a perception-oriented maritime simulation and data-generation platform built on Unreal Engine 5 and Project AirSim. It provides island, open-sea, and port environments; configurable weather, time of day, and wave conditions; a diverse vessel asset library; and spline-based multi-vessel motion. MMUSV-Sim acquires RGB, depth, semantic, LiDAR, and radar observations across multiple USVs and captures a common world state for per-agent annotation export. Experiments verify that the configured wave settings produce the intended changes in vessel heave, roll, and pitch, and evaluate the geometric consistency between projected annotations and semantic renderings. In LiDAR-based cooperative BEV vessel detection experiments on the generated multi-USV dataset, Early Fusion achieves an [email protected] of 72.74, compared with 45.54 using a single USV.
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