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March 19, 2025
The development of Embodied AI, i.e., artificial intelligence that operates in a physical or simulated environment, requires large quantities of high-quality 3D models, particularly of objects with moving parts (articulated objects). Existing methods for creating such models, however, are reaching their limits. Data-driven approaches depend on the quantity and quality of training data, while simulation-based methods often require a high degree of manual effort and the physical accuracy of the results is not always guaranteed.
A new method called "Infinite Mobility" promises a remedy. It relies on procedural generation to create articulated objects with high fidelity and physically plausible properties. In contrast to data-driven methods, which learn from existing examples, procedural generation is based on algorithms that generate objects based on defined rules and parameters. This allows for the creation of a nearly unlimited number of variations and combinations.
The developers of Infinite Mobility emphasize the scalability and the high quality of the generated objects. Both user studies and quantitative evaluations show that the results are comparable to human-created datasets in terms of physical properties and mesh quality and are superior to existing methods. The generated objects exhibit realistic movement patterns and can be used in physical simulations.
Another advantage of Infinite Mobility lies in the possibility of using the generated data for training generative models. This opens up new perspectives for scaling the creation of 3D objects and could significantly accelerate the development of Embodied AI applications. By training generative models with the synthetic data, they can learn to generate similar objects independently, thus reducing the need for manually created models.
The technology behind Infinite Mobility has the potential to fundamentally change the way 3D models are created. The combination of procedural generation and the ability to train generative models enables the efficient and scalable creation of high-quality, articulated objects. This could have far-reaching implications for various application areas, from the development of robots and autonomous vehicles to the creation of virtual worlds and games.
Mindverse, as a provider of AI-powered content solutions, is following the developments in the field of 3D model generation with great interest. Procedural generation and especially approaches like Infinite Mobility open up new possibilities for the automated creation of content and could further advance the development of customized AI solutions such as chatbots, voicebots, and AI search engines.
Bibliography: - https://arxiv.org/abs/2503.13424 - https://arxiv.org/html/2503.13424v1 - https://synthical.com/article/Infinite-Mobility%3A-Scalable-High-Fidelity-Synthesis-of-Articulated-Objects-via-Procedural-Generation-97efe042-c907-4e64-a754-79d268589013? - http://paperreading.club/page?id=292800 - https://www.reddit.com/r/ninjasaid13/comments/1jdx3mr/250313424_infinite_mobility_scalable_highfidelity/ - https://eccv.ecva.net/virtual/2024/session/90 - https://3dvconf.github.io/2024/accepted-papers/ - https://ras.papercept.net/conferences/conferences/IROS24/program/IROS24_ContentListWeb_3.html - https://aaai.org/wp-content/uploads/2025/01/AAAI-25-Poster-Schedule.pdf