[Submitted on 14 Aug 2026 (v1), last revised 4 Nov 2026 (this version, v2)]
Abstract:Perception from a single unmanned surface vehicle (USV) is limited by sensing range, field of view, and occlusions caused by islands, port infrastructure, and nearby vessels. Multi-USV cooperative perception can alleviate these limitations by integrating complementary observations from distributed viewpoints. However, progress is constrained by the high cost of coordinated sea trials, the scarcity of multi-USV datasets, and the lack of integrated maritime simulation and evaluation tools. We present MMUSV-Sim, a perception-oriented maritime simulation and data-generation platform built on Unreal Engine 5 and Project AirSim. It supports configurable maritime scenarios, synchronized multimodal acquisition across multiple USVs, and consistent 3D annotations in a shared world frame. Using MMUSV-Sim, we construct MarU2U-200m, a synchronized multi-USV RGB–LiDAR dataset with 341 sequences and 14,385 scene frames. We establish a cooperative bird’s-eye-view (BEV) vessel detection benchmark with LiDAR and RGB–LiDAR inputs. Experimental results show that Early Fusion improves LiDAR detection AP@0.5 from 64.26 to 81.46 compared with the single-USV baseline. RGB features further improve intermediate fusion, increasing AP@0.5 by up to 4.55 percentage points. LiDAR and RGB transfer experiments also show the value of the generated data as a pretraining source for real maritime detection. The project are available at this https URL
Submission history
From: Ziao Li [view email]
[v1] Fri, 14 Aug 2026 11:32:30 UTC (4,309 KB)
[v2] Wed, 4 Nov 2026 12:27:56 UTC (3,873 KB)
