activity
20242026
most citedVLA-OS: Structuring and Dissecting Planning Representations and Paradigms in Vision-Language-Action Models

1 citations · 3 across the 11 of their papers we have counts for

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6 papers · 1 filter

cs.RO2024

TelePreview: A User-Friendly Teleoperation System with Virtual Arm Assistance for Enhanced Effectiveness

Jingxiang Guo, Jiayu Luo, Zhenyu Wei +5

Teleoperation provides an effective way to collect robot data, which is crucial for learning from demonstrations. In this field, teleoperation faces several key challenges: user-fr…

cs.RO2024

FLIP: Flow-Centric Generative Planning as General-Purpose Manipulation World Model

Chongkai Gao, Haozhuo Zhang, Zhixuan Xu +2

We aim to develop a model-based planning framework for world models that can be scaled with increasing model and data budgets for general-purpose manipulation tasks with only langu…

cs.RO2024★ 1 cited

ET-SEED: Efficient Trajectory-Level SE(3) Equivariant Diffusion Policy

Chenrui Tie, Yue Chen, Ruihai Wu +4

Imitation learning, e.g., diffusion policy, has been proven effective in various robotic manipulation tasks. However, extensive demonstrations are required for policy robustness an…

cs.RO2024

Grasp: A Unified Representation of Robot and Object Interaction for Cross-Embodiment Dexterous Grasping

Zhenyu Wei, Zhixuan Xu, Jingxiang Guo +5

Dexterous grasping is a fundamental yet challenging skill in robotic manipulation, requiring precise interaction between robotic hands and objects. In this paper, we present $\math…

cs.RO2024

ManiFoundation Model for General-Purpose Robotic Manipulation of Contact Synthesis with Arbitrary Objects and Robots

Zhixuan Xu, Chongkai Gao, Zixuan Liu +10

To substantially enhance robot intelligence, there is a pressing need to develop a large model that enables general-purpose robots to proficiently undertake a broad spectrum of man…

cs.RO2024★ 1 cited

RiEMann: Near Real-Time SE(3)-Equivariant Robot Manipulation without Point Cloud Segmentation

Chongkai Gao, Zhengrong Xue, Shuying Deng +4

We present RiEMann, an end-to-end near Real-time SE(3)-Equivariant Robot Manipulation imitation learning framework from scene point cloud input. Compared to previous methods that r…