Diffusion policy: Visuomotor policy learning via action diffusion
This paper introduces Diffusion Policy, a new way of generating robot behavior by
representing a robot's visuomotor policy as a conditional denoising diffusion process. We …
representing a robot's visuomotor policy as a conditional denoising diffusion process. We …
Scaling up and distilling down: Language-guided robot skill acquisition
We present a framework for robot skill acquisition, which 1) efficiently scale up data
generation of language-labelled robot data and 2) effectively distills this data down into a …
generation of language-labelled robot data and 2) effectively distills this data down into a …
Combo: Conservative offline model-based policy optimization
Abstract Model-based reinforcement learning (RL) algorithms, which learn a dynamics
model from logged experience and perform conservative planning under the learned model …
model from logged experience and perform conservative planning under the learned model …
What matters in learning from offline human demonstrations for robot manipulation
Imitating human demonstrations is a promising approach to endow robots with various
manipulation capabilities. While recent advances have been made in imitation learning and …
manipulation capabilities. While recent advances have been made in imitation learning and …
Rambo-rl: Robust adversarial model-based offline reinforcement learning
Offline reinforcement learning (RL) aims to find performant policies from logged data without
further environment interaction. Model-based algorithms, which learn a model of the …
further environment interaction. Model-based algorithms, which learn a model of the …
Accelerating reinforcement learning with learned skill priors
Intelligent agents rely heavily on prior experience when learning a new task, yet most
modern reinforcement learning (RL) approaches learn every task from scratch. One …
modern reinforcement learning (RL) approaches learn every task from scratch. One …
Mimicplay: Long-horizon imitation learning by watching human play
Imitation learning from human demonstrations is a promising paradigm for teaching robots
manipulation skills in the real world. However, learning complex long-horizon tasks often …
manipulation skills in the real world. However, learning complex long-horizon tasks often …
Viola: Imitation learning for vision-based manipulation with object proposal priors
We introduce VIOLA, an object-centric imitation learning approach to learning closed-loop
visuomotor policies for robot manipulation. Our approach constructs object-centric …
visuomotor policies for robot manipulation. Our approach constructs object-centric …
Xskill: Cross embodiment skill discovery
Human demonstration videos are a widely available data source for robot learning and an
intuitive user interface for expressing desired behavior. However, directly extracting …
intuitive user interface for expressing desired behavior. However, directly extracting …
Augmenting reinforcement learning with behavior primitives for diverse manipulation tasks
Realistic manipulation tasks require a robot to interact with an environment with a prolonged
sequence of motor actions. While deep reinforcement learning methods have recently …
sequence of motor actions. While deep reinforcement learning methods have recently …