[PDF][PDF] Grounding language in play
C Lynch, P Sermanet - arXiv preprint arXiv:2005.07648, 2020 - academia.edu
Natural language is perhaps the most versatile and intuitive way for humans to communicate
tasks to a robot. Prior work on Learning from Play (LfP)(Lynch et al., 2019) provides a simple …
tasks to a robot. Prior work on Learning from Play (LfP)(Lynch et al., 2019) provides a simple …
Language conditioned imitation learning over unstructured data
C Lynch, P Sermanet - arXiv preprint arXiv:2005.07648, 2020 - arxiv.org
Natural language is perhaps the most flexible and intuitive way for humans to communicate
tasks to a robot. Prior work in imitation learning typically requires each task be specified with …
tasks to a robot. Prior work in imitation learning typically requires each task be specified with …
What matters in language conditioned robotic imitation learning over unstructured data
A long-standing goal in robotics is to build robots that can perform a wide range of daily
tasks from perceptions obtained with their onboard sensors and specified only via natural …
tasks from perceptions obtained with their onboard sensors and specified only via natural …
Rt-h: Action hierarchies using language
Language provides a way to break down complex concepts into digestible pieces. Recent
works in robot imitation learning use language-conditioned policies that predict actions …
works in robot imitation learning use language-conditioned policies that predict actions …
Learning language-conditioned robot behavior from offline data and crowd-sourced annotation
We study the problem of learning a range of vision-based manipulation tasks from a large
offline dataset of robot interaction. In order to accomplish this, humans need easy and …
offline dataset of robot interaction. In order to accomplish this, humans need easy and …
Playfusion: Skill acquisition via diffusion from language-annotated play
Learning from unstructured and uncurated data has become the dominant paradigm for
generative approaches in language or vision. Such unstructured and unguided behavior …
generative approaches in language or vision. Such unstructured and unguided behavior …
Incremental learning of humanoid robot behavior from natural interaction and large language models
L Bärmann, R Kartmann, F Peller-Konrad… - arXiv preprint arXiv …, 2023 - arxiv.org
Natural-language dialog is key for intuitive human-robot interaction. It can be used not only
to express humans' intents, but also to communicate instructions for improvement if a robot …
to express humans' intents, but also to communicate instructions for improvement if a robot …
Lila: Language-informed latent actions
Abstract We introduce Language-Informed Latent Actions (LILA), a framework for learning
natural language interfaces in the context of human-robot collaboration. LILA falls under the …
natural language interfaces in the context of human-robot collaboration. LILA falls under the …
Do as i can, not as i say: Grounding language in robotic affordances
M Ahn, A Brohan, N Brown, Y Chebotar… - arXiv preprint arXiv …, 2022 - arxiv.org
Large language models can encode a wealth of semantic knowledge about the world. Such
knowledge could be extremely useful to robots aiming to act upon high-level, temporally …
knowledge could be extremely useful to robots aiming to act upon high-level, temporally …
[HTML][HTML] Do as i can, not as i say: Grounding language in robotic affordances
A Brohan, Y Chebotar, C Finn… - … on robot learning, 2023 - proceedings.mlr.press
Large language models can encode a wealth of semantic knowledge about the world. Such
knowledge could be extremely useful to robots aiming to act upon high-level, temporally …
knowledge could be extremely useful to robots aiming to act upon high-level, temporally …