Text2Robot: Evolutionary robot design from text descriptions

Authors: R.P. Ringel¹, Z.S. Charlick¹, J. Liu¹, B. Xia¹, B. Chen¹

¹Duke University

Publication: 2025 IEEE International Conference on Robotics and Automation (ICRA), pp. 5789–5797 (2025)

Presentation: Poster

DOI: 10.1109/ICRA55743.2025.11128168

Abstract

Robot design has traditionally been costly and labor-intensive. Despite advancements in automated processes, it remains challenging to navigate a vast design space while producing physically manufacturable robots. We introduce Text2Robot, a framework that converts user text specifications and performance preferences into physical quadrupedal robots. Within minutes, Text2Robot can use text-to-3D models to provide strong initializations of diverse morphologies. Within a day, our geometric processing algorithms and body-control co-optimization produce a walking robot by explicitly considering real-world electronics and manufacturability. Text2Robot enables rapid prototyping and opens new opportunities for robot design with generative models. Our website is at http://generalroboticslab.com/Text2Robot/.

Paper

Citation

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@inproceedings{ringel2025text2robot,
  title={Text2Robot: Evolutionary robot design from text descriptions},
  author={Ringel, R.P. and Charlick, Z.S. and Liu, J. and Xia, B. and Chen, B.},
  booktitle={2025 IEEE International Conference on Robotics and Automation (ICRA)},
  pages={5789--5797},
  year={2025},
  organization={IEEE}
}