[VCC-ALIFE 2024] Text2Robot: Evolutionary Robot Design from Text Descriptions 

Virtual Creature Competition Submission: Text2Robot: Evolutionary Robot Design from Text Descriptions. Duke General Robotics Lab.
Authors: Ryan P. Ringel∗, Zachary S. Charlick∗, Jiaxun Liu∗, Boxi Xia, Boyuan Chen. (* denotes equal contribution)
Full Project website (paper, code, hardware manual, video): generalrobotics...
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.