An Autonomous GeoAI Agent for Arctic Eco-Navigation

用于北极生态导航的自主地理人工智能（GeoAI）代理

Arctic maritime navigation is becoming increasingly important as changing sea-ice conditions expand seasonal accessibility while simultaneously introducing substantial operational, environmental, and community risks. Arctic route planning is inherently a multi-criteria problem: routes that improve vessel safety or efficiency may increase exposure to sea ice, sensitive ecosystems, or nearby communities.

随着海冰状况的变化扩大了季节性通航能力，北极海上航行变得日益重要，但同时也带来了巨大的运营、环境和社区风险。北极航线规划本质上是一个多准则问题：旨在提高船舶安全或效率的航线，可能会增加船舶暴露于海冰、敏感生态系统或附近社区的风险。

Existing routing methods prioritize travel time, fuel use, and navigational risk, often overlooking ecological and community impacts. We introduce a human-in-the-loop, multi-agent GeoAI system for Arctic eco-navigation that integrates operational, physical, ecological, and community-related criteria within a unified routing framework.

现有的航线规划方法优先考虑航行时间、燃料消耗和航行风险，往往忽视了生态和社区影响。我们引入了一种用于北极生态导航的“人在回路”（human-in-the-loop）多代理地理人工智能（GeoAI）系统，该系统在一个统一的路由框架内整合了运营、物理、生态和社区相关的准则。

Multiple specialized agents coordinate geospatial data acquisition and preparation, multi-objective route generation, and skyline-based decision support. The ecological criteria explicitly account for exposure to sensitive areas, including Essential Fish Habitat and seal critical habitat.

多个专业代理协同负责地理空间数据的获取与准备、多目标航线生成以及基于天际线（skyline-based）的决策支持。生态准则明确考虑了对敏感区域的暴露影响，包括重要鱼类栖息地和海豹关键栖息地。

By considering these ecosystem impacts and potential community burdens while keeping consequential value judgments under human control, the framework supports safer, more transparent, and socially responsible Arctic navigation. Project page and code are publicly available.

通过在将重要的价值判断置于人类控制之下的同时，综合考虑这些生态系统影响和潜在的社区负担，该框架支持更安全、更透明且具有社会责任感的北极航行。项目页面和代码现已公开。