A review of robot learning for manipulation: Challenges, representations, and algorithms

O Kroemer, S Niekum, G Konidaris - Journal of machine learning research, 2021‏ - jmlr.org
A key challenge in intelligent robotics is creating robots that are capable of directly
interacting with the world around them to achieve their goals. The last decade has seen …

On the use of simulation in robotics: Opportunities, challenges, and suggestions for moving forward

HS Choi, C Crump, C Duriez, A Elmquist… - Proceedings of the …, 2021‏ - pnas.org
The last five years marked a surge in interest for and use of smart robots, which operate in
dynamic and unstructured environments and might interact with humans. We posit that well …

Rt-2: Vision-language-action models transfer web knowledge to robotic control

A Brohan, N Brown, J Carbajal, Y Chebotar… - arxiv preprint arxiv …, 2023‏ - arxiv.org
We study how vision-language models trained on Internet-scale data can be incorporated
directly into end-to-end robotic control to boost generalization and enable emergent …

[HTML][HTML] Rt-2: Vision-language-action models transfer web knowledge to robotic control

B Zitkovich, T Yu, S Xu, P Xu, T **ao… - … on Robot Learning, 2023‏ - proceedings.mlr.press
We study how vision-language models trained on Internet-scale data can be incorporated
directly into end-to-end robotic control to boost generalization and enable emergent …

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration0

A O'Neill, A Rehman, A Maddukuri… - … on Robotics and …, 2024‏ - ieeexplore.ieee.org
Large, high-capacity models trained on diverse datasets have shown remarkable successes
on efficiently tackling downstream applications. In domains from NLP to Computer Vision …

Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning

T Yu, D Quillen, Z He, R Julian… - … on robot learning, 2020‏ - proceedings.mlr.press
Meta-reinforcement learning algorithms can enable robots to acquire new skills much more
quickly, by leveraging prior experience to learn how to learn. However, much of the current …

Mimicgen: A data generation system for scalable robot learning using human demonstrations

A Mandlekar, S Nasiriany, B Wen, I Akinola… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Imitation learning from a large set of human demonstrations has proved to be an effective
paradigm for building capable robot agents. However, the demonstrations can be extremely …

Gapartnet: Cross-category domain-generalizable object perception and manipulation via generalizable and actionable parts

H Geng, H Xu, C Zhao, C Xu, L Yi… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
For years, researchers have been devoted to generalizable object perception and
manipulation, where cross-category generalizability is highly desired yet underexplored. In …

On bringing robots home

NMM Shafiullah, A Rai, H Etukuru, Y Liu, I Misra… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Throughout history, we have successfully integrated various machines into our homes.
Dishwashers, laundry machines, stand mixers, and robot vacuums are a few recent …

Sim-to-real transfer of robotic control with dynamics randomization

XB Peng, M Andrychowicz, W Zaremba… - … on robotics and …, 2018‏ - ieeexplore.ieee.org
Simulations are attractive environments for training agents as they provide an abundant
source of data and alleviate certain safety concerns during the training process. But the …