发表机构
Chung-Ang University; Hanyang University; Carnegie Mellon University; KAIST（中央大学; 汉阳大学; 卡内基梅隆大学; 韩国科学技术院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对固定控制器下任务抽象因空间布局不可执行的问题，提出将任务需求编译为仿射约束并仅修复连续坐标的布局修复方法，经双后端认证与300次rollout验证有效。
AI 中文摘要
任务抽象可以指定预期事件，而其空间布局会阻止固定的智能体和控制器完成这些事件。从提供的结构化任务记录出发，我们将整体任务跟踪、间隙和执行要求编译为可审计的仿射布局约束。我们仅修复声明的连续坐标，保留事件顺序、时序、拓扑和控制器。最违反行更新允许条件性有限认证和净位移界限；同编译器二次投影将表示与优化器分离。在三个研究者撰写的任务抽象上，两个后端均认证所有三个布局，并各自完成全部300次新鲜配对 rollout。风险目标扫描还暴露了固定事件测试，所选证书无法仅通过布局编辑满足这些测试。
英文摘要
A task abstraction can specify the intended events while its spatial layout prevents a fixed agent and controller from completing them. Starting from a supplied structured task record, we compile whole-task tracking, clearance, and actuation requirements into auditable affine layout constraints. We repair only declared continuous coordinates, preserving event order, timing, topology, and the controller. A most-violated-row update admits conditional finite-certification and net-displacement bounds; a same-compiler quadratic projection separates the representation from the optimizer. On three researcher-authored task abstractions, both backends certify all three layouts and complete all 300 fresh paired rollouts per backend. A risk-target sweep also exposes fixed event tests that the chosen certificate cannot satisfy through layout edits alone.
Comments17 pages, 8 figures, 10 tables
