信任、几何与规则：面向不确定性下安全USV导航的可信度感知强化学习框架

Yuhang Zhang, Shuqi Chai, Yukang Zhang, Liusha Yang, Mingchuan Zhang, Wei Wang, Qingjiang Shi, Quanbo Ge

2026

摘要

提出一种集成可信度加权值学习、协方差膨胀速度障碍和风险感知COLREGs职责嵌入的强化学习框架，解决无人水面艇在动态海事环境中因感知不确定性导致的策略过拟合和规则离散性问题。通过动态信任因子和几何安全屏蔽，显著提升训练鲁棒性和避碰合规性。

credibility-aware reinforcement learningUSV navigationCOLREGsgeometric safety shieldinguncertainty estimation

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