Ethical awareness is critical for robots operating in human environments, yet existing automated planning tools provide little support. Manually specifying ethical rules is labour-intensive and highly context-specific. We present Principles2Plan, an interactive research prototype demonstrating how a human and a Large Language Model (LLM) can collaborate to produce context-sensitive ethical rules and guide automated planning. A domain expert provides the planning domain, problem details, and relevant high-level principles such as beneficence and privacy. The system generates operationalisable ethical rules consistent with these principles, which the user can review, prioritise, and supply to a planner to produce ethically-informed plans. To our knowledge, no prior system supports users in generating principle-grounded rules for classical planning contexts. Principles2Plan showcases the potential of human-LLM collaboration for making ethical automated planning more practical and feasible.

翻译：伦理意识对于在人类环境中运行的机器人至关重要，然而现有的自动化规划工具对此支持甚少。人工指定伦理规则不仅劳动密集，且高度依赖具体情境。本文提出Principles2Plan——一个交互式研究原型，展示了人类与大语言模型如何协作生成情境敏感的伦理规则并指导自动化规划。领域专家提供规划领域、问题细节及相关高层原则（如行善原则与隐私原则）。系统生成与这些原则一致且可操作的伦理规则，用户可对其进行审查、优先级排序，并提交给规划器以生成符合伦理的规划方案。据我们所知，尚无先例系统支持用户在经典规划情境中生成基于原则的规则。Principles2Plan展现了人机协作在推动伦理自动化规划走向实用化与可行化方面的潜力。