Concept2robot: Learning manipulation concepts from instructions and human demonstrations
We aim to endow a robot with the ability to learn manipulation concepts that link natural
language instructions to motor skills. Our goal is to learn a single multi-task policy that takes …
language instructions to motor skills. Our goal is to learn a single multi-task policy that takes …
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 …
Language-conditioned imitation learning for robot manipulation tasks
Imitation learning is a popular approach for teaching motor skills to robots. However, most
approaches focus on extracting policy parameters from execution traces alone (ie, motion …
approaches focus on extracting policy parameters from execution traces alone (ie, motion …
Lancon-learn: Learning with language to enable generalization in multi-task manipulation
Robots must be capable of learning from previously solved tasks and generalizing that
knowledge to quickly perform new tasks to realize the vision of ubiquitous and useful robot …
knowledge to quickly perform new tasks to realize the vision of ubiquitous and useful robot …
Robotic skill acquisition via instruction augmentation with vision-language models
In recent years, much progress has been made in learning robotic manipulation policies that
follow natural language instructions. Such methods typically learn from corpora of robot …
follow natural language instructions. Such methods typically learn from corpora of robot …
Learning by watching: Physical imitation of manipulation skills from human videos
Learning from visual data opens the potential to accrue a large range of manipulation
behaviors by leveraging human demonstrations without specifying each of them mathe …
behaviors by leveraging human demonstrations without specifying each of them mathe …
Guiding multi-step rearrangement tasks with natural language instructions
Enabling human operators to interact with robotic agents using natural language would
allow non-experts to intuitively instruct these agents. Towards this goal, we propose a novel …
allow non-experts to intuitively instruct these agents. Towards this goal, we propose a novel …
Bottom-up skill discovery from unsegmented demonstrations for long-horizon robot manipulation
We tackle real-world long-horizon robot manipulation tasks through skill discovery. We
present a bottom-up approach to learning a library of reusable skills from unsegmented …
present a bottom-up approach to learning a library of reusable skills from unsegmented …
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 …
Bridgedata v2: A dataset for robot learning at scale
We introduce BridgeData V2, a large and diverse dataset of robotic manipulation behaviors
designed to facilitate research in scalable robot learning. BridgeData V2 contains 53,896 …
designed to facilitate research in scalable robot learning. BridgeData V2 contains 53,896 …