Code as Policy: Language Models as Policy Generators for Robot Manipulation

摘要

We propose Code as Policies (CaP), a method that uses large language models to generate robot policy code from natural language instructions. CaP composes robot manipulation APIs through code generation, enabling flexible task specification and generalization to novel tasks without retraining. The approach demonstrates strong performance on tabletop manipulation tasks and can adapt to new environments and instructions at inference time.