RIGOR: CONSTRAINT-AWARE LAYOUT PLANNING AND GUI GROUNDING FOR INDUSTRIAL SCENES

Constructing an industrial scene through a graphical interface requires both a coherent spatial target and actions that realize its device parameters. Accurate interaction cannot compensate for an unsuitable layout, while a suitable layout can still be misapplied to the wrong interface field. We introduce Rigor, a dataset and framework for studying these complementary requirements in static Unity workcells. The dataset links 1,050 rule-validated layouts from 291 task seeds to 222,306 GUI action units from 938 verified expert trajectories. The framework connects a supervised coordinate planner, relation-informed candidate generation, and bounded local search to a separately trained action model through explicit device-level targets. Refinement uses deterministic task feedback at inference time. Stage-wise evaluation separates layout quality from next-action correctness on frozen GUI states with shared targets. Rigor achieves 87.04 in layout quality and 79.69 in relation satisfaction, compared with 54.14 and 29.17 for the best respective baselines, and 81.14% step success under the given-target protocol. Planning ablations improve layout quality from 25.85 with coordinate supervision to 87.04 with both refinement stages. These results support explicit constraint coordination and distinguish action recognition from parameter-grounded progress in GUI-based construction.