Recently Published by Autodesk Researchers

Autodesk Research teams regularly contribute to peer-reviewed scientific journals and present at conferences around the world. Check out some recent publications from Autodesk Researchers.

PlotMap: Automated Layout Design for Building Game World

World-building plays a vital role in the game’s experience, with game maps that masterfully intertwine with and elevate the narrative captivating players and leaving a lasting impression. However, designing game maps that support a desired narrative is challenging, as it requires satisfying complex constraints from various considerations. In this work, the team introduces an extra layer of plot facility layout design that is independent of the underlying map generation method in a world-building pipeline. In doing so, the team defines (plot) facility layout tasks as the tasks of assigning concrete locations on a game map to abstract locations mentioned in a given story (plot facilities), following spatial constraints derived from the story. The goal is to develop a method of generating datasets of facility layout tasks, create a gym-like environment for experimenting with and evaluating different methods, and further analyze the two methods with comprehensive experiments, aiming to provide insights for solving facility layout tasks.

Inspired by AI? A Novel Generative AI System to Assist Conceptual Automotive Design

Design inspiration is crucial for establishing the direction of a design as well as evoking feelings and conveying meanings during the conceptual design process. Many practice designers use text-based searches on platforms like Pinterest to gather image ideas, followed by sketching on paper or using digital tools to develop concepts. Emerging generative AI techniques, such as diffusion models, offer a promising avenue to streamline these processes by swiftly generating design concepts based on text and image inspiration inputs, subsequently using the AI generated design concepts as fresh sources of inspiration for further concept development. However, applying these generative AI techniques directly within a design context has challenges. In this research, the team conducted workshops, surveys, and data augmentation involving teams of experienced automotive designers to investigate their current practices in generating concepts inspired by texts and images, as well as their preferred interaction modes for generative AI systems to support the concept generation workflow.

What’s in this LCA Report? A Case Study on Harnessing Large Language Models to Support Designers in Understanding Life Cycle Reports

Life cycle assessment (LCA) is a well-established approach and benchmark for design for sustainability efforts, in which detailed reports are produced that can serve as decision-making guides for developing new products. However, LCA reports are typically dense and technically complex, making it difficult for many engineering design project stakeholders to appropriately leverage the information found within them. This work seeks to understand and improve the transfer of knowledge from LCA reports during the early stages of the design process, specifically leveraging the natural language capabilities of large language models (LLMs). In this paper, the team investigates how four LCA- and sustainability-centric prompting frameworks can extract relevant design knowledge from LCA reports, demonstrated through a case study where an LLM (ChatGPT) is prompted on a provided electric toothbrush LCA report.