Constraint-Aware Graphical Layout Generation With Placement Scoring

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing procedural content generation methods struggle with constraint satisfaction in generating graphical layouts, as constraints are not evaluated until the end of the generation process, leading to inefficiencies and inaccuracies.

Innovation Solution

A method and system that determine placement probability scores for each cell in a grid structure, adjust scores based on predefined constraints, and place objects in constraint-free cells with the highest adjusted probability, using an AI model to automate the layout generation process.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If denoising diffusion models are used to generate layouts, then the generation process can proceed in a continuous domain, but constraint satisfaction becomes problematic as constraints cannot be evaluated until the end of generation at discretization

Engineering Contradiction:

Improveautomated layout generationVSAvoidconstraint satisfaction

Core Design Contradiction:

Extent of automationVSManufacturing precision

Solution Approach 1:

The patent applies preliminary action by evaluating constraints at each discrete time step during the generation process rather than waiting until the end. The system discretizes the continuous generation process into time steps t=0 to T, and at each step evaluates whether placing an object in a cell would violate any constraints. This early evaluation prevents constraint violations from propagating through the entire generation process, ensuring final layout satisfaction while maintaining automated generation.

Inventive Principle:

Principle #10Preliminary action

2Device complexity

If constraints are evaluated only at the end of generation, then the generation process is simpler, but constraint satisfaction accuracy deteriorates

Engineering Contradiction:

Improvegeneration process complexityVSAvoidconstraint satisfaction accuracy

Core Design Contradiction:

Device complexityVSManufacturing precision

Solution Approach 1:

The patent implements feedback by continuously monitoring constraint satisfaction at each time step during object placement. The system calculates a constraint satisfaction score based on the current layout state and compares it against required constraints. If constraints are violated or at risk of violation, the system adjusts the placement probability scores accordingly, providing real-time feedback that guides the generation process toward constraint-satisfying solutions rather than evaluating constraints only after generation completes.

Inventive Principle:

Principle #23Feedback

3Manufacturing precision

If placement probability scores are adjusted based on constraints at each time step, then constraint satisfaction improves, but computational time and memory requirements increase

Engineering Contradiction:

Improveconstraint satisfactionVSAvoidgeneration time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The patent applies partial action by adjusting placement probability scores for only those cells that are relevant to current constraints, rather than recalculating all probabilities globally at each step. The system identifies constrained cells where constraint violations would occur and adjusts only those specific probability scores, leaving other cells unchanged. This selective adjustment reduces computational overhead while maintaining constraint satisfaction accuracy.

Inventive Principle:

Principle #16Partial or excessive action

4Adaptability or versatility

If continuous domain generation is used, then generation flexibility is improved, but constraint evaluation timing becomes problematic

Engineering Contradiction:

Improvegeneration flexibilityVSAvoidconstraint evaluation timing

Core Design Contradiction:

Adaptability or versatilityVSManufacturing precision

Solution Approach 1:

The patent segments the continuous generation process into discrete time steps t=0 to T, where each step represents a discrete state of the layout generation. This segmentation allows the system to maintain the flexibility of continuous domain generation while introducing discrete evaluation points where constraints can be checked. The placement probability scores are updated at each discrete step based on current layout state, enabling constraint evaluation without sacrificing the adaptability of the continuous generation process.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20250319395A1Method and system for generating graphical layout

Publication Date: 2025.10.16 SUPERCELL

AI summary

Disclosed is method including receiving input graphical layout having cells forming grid structure cells are configured to be placed with objects to form GL; determining placement probability score for cells with respect to objects at first point in time; placing each object into IGL for forming GL, wherein placing given object into IGL include selecting given object, based on predefined placement schedule; identifying constrained cell(s) from amongst cells where predefined constraint(s) is violated if given object is placed thereon; adjusting placement probability score, for constrained cell(s), to be zero; adjusting placement probability score, for each cell of constraint-free cells, based on placement probability score for each cell of CFCs, and adjusted placement probability score for constrained cell(s), wherein given object is placed in constraint-free cell (C4) having highest adjusted placement probability score amongst CFCs.