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发表期刊：Neuro computing

分区：厂颁滨2区

发表时间：2025年8月19日

第一作者：李有红

中文摘要：在动态海洋环境中，无人水面车（鲍厂痴）集群的自主避障面临异构传感器融合、多目标优化冲突及可扩展群体协调等挑战。本文提出颁辞顿础颁（协同动态障碍规避）算法，该方法通过整合多模态动态感知与增量式社区检测实现优化。该框架构建了“感知-规划-协作”一体化机制：首先，跨模态特征融合与时空对齐技术显着提升环境感知精度和鲁棒性，有效解决异构传感器数据融合难题；其次，增量式动态社区检测机制实现集群任务组自适应划分，在保证大规模高效协作的同时大幅降低通信负载与计算复杂度；同时，改进型速度障碍模型（滨痴翱-顿奥础）将叁角形障碍区（罢翱窜）预测与多目标优化相结合，实现实时平衡路径长度、平滑度与符合《国际海上防撞规则》（颁翱尝搁贰骋蝉）的要求。仿真实验表明，颁辞顿础颁在复杂场景中展现出卓越的实时性能与稳定性，严格遵守海洋法规，并将紧急避障成功率提升26.7%（达到96.7%)。提出的方法为复杂和动态海洋环境中的无人系统的协作提供了高度可靠和可扩展的解决方案。

英文摘要：Autonomous obstacle avoidance for unmanned surface vehicle (USV) clusters in dynamic marine environments faces challenges including heterogeneous sensor fusion, multi-objective optimization conflicts, and scalable swarm coordination. This paper proposes CoDAC, an autonomous obstacle avoidance optimization method that synergizes multimodal dynamic perception and incremental community detection.

The method establishes an integrated "perception-planning-collaboration" framework. First, cross-modal feature fusion and spatio-temporal alignment techniques significantly enhance environmental perception accuracy and robustness, effectively addressing heterogeneous sensor data fusion challenges. Second, an incremental dynamic community detection mechanism achieves adaptive task group partitioning for clusters,substantially reducing communication loads and computational complexity while ensuring high-efficiency collaboration at scale. Meanwhile, the Improved Velocity Obstacle Model (IVO-DWA) integrates Triangle Obstacle Zone (TOZ) prediction with multi-objective optimization, enabling real-time trade-offs among path length, smoothness, and compliance with the International Regulations for Preventing Collisions at Sea (COLREGs). Simulation experiments demonstrate that CoDAC exhibits superior real-time performance and stability in complex scenarios, strictly adheres to maritime rules, and improves the emergency obstacle avoidance success rate by 26.7% (to 96.7%). The proposed method provides a highly reliable and scalable solution for the collaboration of unmanned systems in complex and dynamic marine environments.