Google's Code-as-Policies Lets Robots Write Their Own Code

Researchers from Google's Robotics team have open-sourced Code-as-Policies (CaP), a robot control method that uses a large language model (LL M) to generate robot-control code that achieves a user-specified goal. CaP uses a hierarchical prompting technique for code generation that outperforms previous methods on the HumanEval code-generation benchmark. The technique and experiments were described in a paper published on arXiv. CaP differs from previous attempts to use LLMs to control robots; instead of generating a sequence of high-level steps or policies to be invoked by the robot, CaP directly generates Python code for those policies. The Google team developed a set of prompting techniques that improved code-generation, including a new hierarchical prompting method.