Video-Language Critic: Transferable Reward Functions for Language-Conditioned Robotics

التفاصيل البيبلوغرافية
العنوان: Video-Language Critic: Transferable Reward Functions for Language-Conditioned Robotics
المؤلفون: Alakuijala, Minttu, McLean, Reginald, Woungang, Isaac, Farsad, Nariman, Kaski, Samuel, Marttinen, Pekka, Yuan, Kai
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Robotics, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
الوصف: Natural language is often the easiest and most convenient modality for humans to specify tasks for robots. However, learning to ground language to behavior typically requires impractical amounts of diverse, language-annotated demonstrations collected on each target robot. In this work, we aim to separate the problem of what to accomplish from how to accomplish it, as the former can benefit from substantial amounts of external observation-only data, and only the latter depends on a specific robot embodiment. To this end, we propose Video-Language Critic, a reward model that can be trained on readily available cross-embodiment data using contrastive learning and a temporal ranking objective, and use it to score behavior traces from a separate reinforcement learning actor. When trained on Open X-Embodiment data, our reward model enables 2x more sample-efficient policy training on Meta-World tasks than a sparse reward only, despite a significant domain gap. Using in-domain data but in a challenging task generalization setting on Meta-World, we further demonstrate more sample-efficient training than is possible with prior language-conditioned reward models that are either trained with binary classification, use static images, or do not leverage the temporal information present in video data.
Comment: 10 pages in the main text, 16 pages including references and supplementary materials. 4 figures and 3 tables in the main text, 1 table in supplementary materials
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2405.19988
رقم الأكسشن: edsarx.2405.19988
قاعدة البيانات: arXiv