多会话多模态水下声学与光学成像测绘
Multi-Session Multimodal Underwater Mapping with Acoustic and Optical Imaging
- Computer Vision and Robotics Research Institute (ViCOROB), University of Girona（赫罗纳大学计算机视觉与机器人研究所（ViCOROB））
- University of Zagreb Faculty of Electrical Engineering and Computing（萨格勒布大学电气工程与计算学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出基于因子图优化的多会话多模态水下测绘框架，联合优化轨迹、地标、外参及对齐变换，在真实数据上显著提升地图一致性，像素准确率提高3.4%。
AI中文摘要：
准确的海底测绘对于海洋科学、考古学和环境监测至关重要。然而，由于定位漂移和传感器偏移，整合来自不同传感器（如侧扫声呐和光学相机）在不同调查会话中收集的数据仍然具有挑战性。本文提出了一种基于因子图优化的多会话、多模态水下测绘框架。该方法联合优化了车辆轨迹、3D地标位置、传感器外参以及每个会话的全局对齐变换。通过将刚性会话间校正与局部轨迹变形相结合，它同时补偿了会话间偏移和由累积导航误差引起的会话内畸变。所提出的方法在加泰罗尼亚海岸收集的真实世界数据集上进行了验证。结果表明，在所有指标（包括像素准确率和平均交并比）上，与未优化和刚性对齐基线相比，地图一致性均有可测量的改进。该方法在像素准确率上比未优化基线提高了3.4%，对应于约14700平方米测绘区域内语义标注的改进。定性结果进一步表明，即使在存在显著轨迹畸变和会话间错位的情况下，声呐和光学地图之间也能实现一致的配准。这些发现证明了所提出框架从异构水下调查中生成连贯多模态海底地图的潜力。
英文摘要：
Accurate seafloor mapping is essential for marine science, archaeology, and environmental monitoring. However, integrating data from different sensors, such as side-scan sonar and optical cameras, collected across separate survey sessions, remains challenging due to positioning drift and sensor offsets. This paper presents a multi-session, multimodal underwater mapping framework based on factor graph optimization. The method jointly optimizes vehicle trajectories, 3D landmark positions, sensor extrinsics, and per-session global alignment transformations. By combining rigid inter-session corrections with local trajectory deformations, it compensates for both inter-session offsets and intra-session distortions from accumulated navigation errors. The proposed methodology was validated on real-world datasets collected along the Catalan coast. Results show measurable improvements in map consistency over both unoptimized and rigid-alignment baselines across all metrics, including Pixel Accuracy and mean Intersection over Union. The method achieves a 3.4% improvement in pixel accuracy over the unoptimized baseline, corresponding to improved semantic labelling across approximately 14700 $\text{m}^2$ of mapped area. Qualitative results further show consistent co-registration between sonar and optical maps, even in the presence of significant trajectory distortions and inter-session misalignments. These findings demonstrate the potential of the proposed framework to generate coherent multimodal seafloor maps from heterogeneous underwater surveys.
