Automatic personalized limbed robot design from media inputs

Designing limbed robots is a complex, multidisciplinary task that typically requires substantial effort from experienced engineers. In this paper, we present a novel automatic robot design framework based on Decomposition-Optimization-Assembling (DOA) to address this challenge. Our framework enables non-experts to create personalized limbed robot designs from media inputs, such as text and images, within minutes to a few hours. Our system leverages recent advances in generative AI and 3D printing to produce designs that match the descriptions provided in the input media. The output consists of selected motors and 3D-printable mechanical components that can be assembled into a limbed robot. To handle the large design space and intricate details in fabrication and assembly, we formulate and solve a series of optimization problems involving actuators, geometry, and structural density. We validate the proposed system by designing and fabricating a Centaur robot based on an image input. Furthermore, we demonstrate the system’s versatility and effectiveness through the generation of a wide variety of limbed robot designs.

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Publication Details

Journal
npj Robotics
Published
2026-06-09
DOI
https://doi.org/10.1038/s44182-026-00101-3
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Automatic personalized limbed robot design from media inputs

Moji Shi, Marija Popović, Gang Chen, Yu Xing et al.
npj Robotics
Soft Robotics and Applications
article

Automatic personalized limbed robot design from media inputs

Moji Shi, Marija Popović, Gang Chen, Yu Xing, Javier Alonso-Mora, Lei Zhang, Jiangmiao Pang
article en

Abstract

Designing limbed robots is a complex, multidisciplinary task that typically requires substantial effort from experienced engineers. In this paper, we present a novel automatic robot design framework based on Decomposition-Optimization-Assembling (DOA) to address this challenge. Our framework enables non-experts to create personalized limbed robot designs from media inputs, such as text and images, within minutes to a few hours. Our system leverages recent advances in generative AI and 3D printing to produce designs that match the descriptions provided in the input media. The output consists of selected motors and 3D-printable mechanical components that can be assembled into a limbed robot. To handle the large design space and intricate details in fabrication and assembly, we formulate and solve a series of optimization problems involving actuators, geometry, and structural density. We validate the proposed system by designing and fabricating a Centaur robot based on an image input. Furthermore, we demonstrate the system’s versatility and effectiveness through the generation of a wide variety of limbed robot designs.

npj Robotics
Shanghai Jiao Tong University (CN), Shanghai Artificial Intelligence Laboratory (CN), Delft University of Technology (NL)
Openalex Percentile: Top 12%
Soft Robotics and Applications
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