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

arXiv 2601.16424 ↗First posted 23 Jan 2026cs.RO cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 39 references that are in the map. First posted on arXiv 23 Jan 2026.

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7 of 39 references.

References · 7

  1. 2016Funnel Libraries for Real-Time Robust Feedback Motion Planningcited by 29
  2. 2017FaSTrack: a Modular Framework for Fast and Guaranteed Safe Motion Planningcited by 23
  3. 2021Chance-Constrained Motion Planning using Modeled Distance-to-Collision Functionscited by 2
  4. 2023Optimal Virtual Tube Planning and Control for Swarm Roboticscited by 2
  5. 2024Open-Source, Cost-Aware Kinematically Feasible Planning for Mobile and Surface Roboticscited by 2
  6. 2023Stranding Risk for Underactuated Vessels in Complex Ocean Currents: Analysis and Controllerscited by 1
  7. 2024Homotopic Path Set Planning for Robot Manipulation and Navigationcited by 1

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