Data-Efficient Learning of Natural Language to Linear Temporal Logic Translators for Robot Task Specification

Abstract

Jiayi Pan, Glen Chou, Dmitry Berenson. ICRA 2023.

We present a learning-based approach to translate from natural language commands to LTL specifications with very limited human-labeled training data by leveraging Large Language Models. Our model can translate natural language commands at 75% accuracy with about 12 annotations and when given full training data, achieves state-of-the-art performance. We also show how its outputs can be used to plan long-horizon, multi-stage tasks on a 12D quadrotor.