We present RENEW, a global path planner for Autonomous Surface Vehicle (ASV) in dynamic environments with external disturbances (e.g., water currents). RENEW introduces a unified risk- and energy-aware strategy that ensures safety by dynamically identifying non-navigable regions and enforcing adaptive safety constraints. Inspired by maritime contingency planning, it employs a best-effort strategy to maintain control under adverse conditions. The hierarchical architecture combines high-level constrained triangulation for topological diversity with low-level trajectory optimization within safe corridors. Validated with real-world ocean data, RENEW is the first framework to jointly address adaptive non-navigability and topological path diversity for robust maritime navigation.

翻译：本文提出RENEW——一种适用于存在外部扰动（如水流）的动态环境的自主水面艇全局路径规划器。RENEW引入了一种统一的风险与能量感知策略，通过动态识别不可航行区域并实施自适应安全约束来保障航行安全。受海上应急规划思想启发，该系统采用尽力而为策略以在恶劣条件下维持控制能力。其分层架构将高层级约束三角剖分（用于拓扑多样性）与低层级安全走廊内的轨迹优化相结合。基于真实海洋数据的验证表明，RENEW是首个同时解决自适应不可航行区域识别与拓扑路径多样性问题的鲁棒海上导航框架。