Language to Design (L2D): Towards Self Evolving Robots

Designing a robot requires expertise in both complex mechanics and control. This process typically relies on slow cycles of estimation, prototyping, and testing to find where design and behavior align. This raises a fundamental question: can robot design be made as simple as describing what we want a robot to do? We present Language to Design (L2D), a co-design framework that turns a prompt and an existing robot into an optimized body, a motion that performs the task, and manufacturable parts, without tuning or training per task or per robot. The framework supports 1) language proposals grounded in measured physics, where language reflection decides what to change and physics measured in simulation decides how much, 2) a continuous design space, spanning link kinematics, motors, added joints, and continuous morphology designs for contact points such as feet and fingers, and 3) real-world fabrication, where prompt with stress-based topology optimization turns added parts into light, manufacturable components can be deployed zero shot on hardware. We demonstrate L2D by co-designing quadrupeds, arms, grippers, dexterous hands, and humanoids across eleven tasks on nine different robots, and deploy a printed design zero shot on a real quadruped for a climbing task. Task videos are available on our anonymous website.