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arXiv:2601.16424

RENEW: Risk- and Energy-Aware Navigation in Dynamic Waterways

RENEW: Risk- and Energy-Aware Navigation in Dynamic Waterways

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著者: Mingi Jeong, Alberto Quattrini Li

分類: cs.RO, cs.AI

原文アブストラクト

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.