[HTML][HTML] A survey on deep reinforcement learning algorithms for robotic manipulation
Robotic manipulation challenges, such as grasping and object manipulation, have been
tackled successfully with the help of deep reinforcement learning systems. We give an …
tackled successfully with the help of deep reinforcement learning systems. We give an …
[HTML][HTML] Review of machine learning methods in soft robotics
Soft robots have been extensively researched due to their flexible, deformable, and adaptive
characteristics. However, compared to rigid robots, soft robots have issues in modeling …
characteristics. However, compared to rigid robots, soft robots have issues in modeling …
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 …
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
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 …
directly into end-to-end robotic control to boost generalization and enable emergent …
R3m: A universal visual representation for robot manipulation
We study how visual representations pre-trained on diverse human video data can enable
data-efficient learning of downstream robotic manipulation tasks. Concretely, we pre-train a …
data-efficient learning of downstream robotic manipulation tasks. Concretely, we pre-train a …
Bc-z: Zero-shot task generalization with robotic imitation learning
E Jang, A Irpan, M Khansari… - … on Robot Learning, 2022 - proceedings.mlr.press
In this paper, we study the problem of enabling a vision-based robotic manipulation system
to generalize to novel tasks, a long-standing challenge in robot learning. We approach the …
to generalize to novel tasks, a long-standing challenge in robot learning. We approach the …
Affordances from human videos as a versatile representation for robotics
Building a robot that can understand and learn to interact by watching humans has inspired
several vision problems. However, despite some successful results on static datasets, it …
several vision problems. However, despite some successful results on static datasets, it …
Open x-embodiment: Robotic learning datasets and rt-x models
Large, high-capacity models trained on diverse datasets have shown remarkable successes
on efficiently tackling downstream applications. In domains from NLP to Computer Vision …
on efficiently tackling downstream applications. In domains from NLP to Computer Vision …
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 …
Mobile aloha: Learning bimanual mobile manipulation with low-cost whole-body teleoperation
Imitation learning from human demonstrations has shown impressive performance in
robotics. However, most results focus on table-top manipulation, lacking the mobility and …
robotics. However, most results focus on table-top manipulation, lacking the mobility and …