Gnfactor: Multi-task real robot learning with generalizable neural feature fields

[PDF] arxiv.org

Robot learning in the era of foundation models: A survey

X Xiao, J Liu, Z Wang, Y Zhou, Y Qi, Q Cheng… - arXiv preprint arXiv …, 2023 - arxiv.org
The proliferation of Large Language Models (LLMs) has s fueled a shift in robot learning
from automation towards general embodied Artificial Intelligence (AI). Adopting foundation …
被引用次数：9 相关文章 所有 4 个版本
[PDF] arxiv.org

3d diffusion policy

Y Ze, G Zhang, K Zhang, C Hu, M Wang… - arXiv preprint arXiv …, 2024 - arxiv.org
Imitation learning provides an efficient way to teach robots dexterous skills; however,
learning complex skills robustly and generalizablely usually consumes large amounts of …
被引用次数：6 相关文章 所有 2 个版本
[PDF] arxiv.org

DFields: Dynamic 3D Descriptor Fields for Zero-Shot Generalizable Robotic Manipulation

Y Wang, Z Li, M Zhang, K Driggs-Campbell… - arXiv preprint arXiv …, 2023 - arxiv.org
Scene representation has been a crucial design choice in robotic manipulation systems. An
ideal representation should be 3D, dynamic, and semantic to meet the demands of diverse …
被引用次数：9 相关文章 所有 5 个版本
[PDF] arxiv.org

Learning generalizable feature fields for mobile manipulation

RZ Qiu, Y Hu, G Yang, Y Song, Y Fu, J Ye, J Mu… - arXiv preprint arXiv …, 2024 - arxiv.org
An open problem in mobile manipulation is how to represent objects and scenes in a unified
manner, so that robots can use it both for navigating in the environment and manipulating …
被引用次数：3 相关文章 所有 2 个版本
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Human-oriented Representation Learning for Robotic Manipulation

M Huo, M Ding, C Xu, T Tian, X Zhu, Y Mu… - arXiv preprint arXiv …, 2023 - arxiv.org
Humans inherently possess generalizable visual representations that empower them to
efficiently explore and interact with the environments in manipulation tasks. We advocate …
被引用次数：4 相关文章 所有 3 个版本
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Sparsedff: Sparse-view feature distillation for one-shot dexterous manipulation

Q Wang, H Zhang, C Deng, Y You, H Dong… - arXiv preprint arXiv …, 2023 - arxiv.org
Humans excel at transferring manipulation skills across diverse object shapes, poses, and
appearances due to their understanding of semantic correspondences between different …
被引用次数：4 相关文章 所有 3 个版本
[PDF] arxiv.org

Manigaussian: Dynamic gaussian splatting for multi-task robotic manipulation

G Lu, S Zhang, Z Wang, C Liu, J Lu, Y Tang - arXiv preprint arXiv …, 2024 - arxiv.org
Performing language-conditioned robotic manipulation tasks in unstructured environments
is highly demanded for general intelligent robots. Conventional robotic manipulation …
被引用次数：3 相关文章 所有 2 个版本
[PDF] arxiv.org

Toward general-purpose robots via foundation models: A survey and meta-analysis

Y Hu, Q Xie, V Jain, J Francis, J Patrikar… - arXiv preprint arXiv …, 2023 - arxiv.org
Building general-purpose robots that can operate seamlessly, in any environment, with any
object, and utilizing various skills to complete diverse tasks has been a long-standing goal in …
被引用次数：17 相关文章 所有 2 个版本
[PDF] arxiv.org

GaussianGrasper: 3D Language Gaussian Splatting for Open-vocabulary Robotic Grasping

Y Zheng, X Chen, Y Zheng, S Gu, R Yang, B Jin… - arXiv preprint arXiv …, 2024 - arxiv.org
Constructing a 3D scene capable of accommodating open-ended language queries, is a
pivotal pursuit, particularly within the domain of robotics. Such technology facilitates robots …
被引用次数：2 相关文章 所有 2 个版本
[PDF] arxiv.org

Fmgs: Foundation model embedded 3d gaussian splatting for holistic 3d scene understanding

X Zuo, P Samangouei, Y Zhou, Y Di, M Li - arXiv preprint arXiv …, 2024 - arxiv.org
Precisely perceiving the geometric and semantic properties of real-world 3D objects is
crucial for the continued evolution of augmented reality and robotic applications. To this end …
被引用次数：10 相关文章 所有 2 个版本