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Text2Robot: Evolutionary Robot Design from Text Descriptions
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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.
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Cited by 1 Pith paper
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VLMgineer: Vision Language Models as Robotic Toolsmiths
VLMgineer combines VLM-generated URDF tool designs with evolutionary search to co-design tools and action plans, outperforming human-specified and existing tools on a new simulated manipulation benchmark.
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