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Chenguang Huang

7 accepted papers

2025

Articulated Object Estimation in the Wild

CoRL 2025poster

Understanding the 3D motion of articulated objects is essential in robotic scene understanding, mobile manipulation, and motion planning. Prior methods for articulation estimation have primarily focused on controlled settings, assuming either fixed camera viewpoints or direct observations of various…

Cited by 0SourceScholar
2025

BYE: Build Your Encoder With One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding

RA-L 2025

Dynamic scene understanding remains a persistent challenge in robotic applications. Early dynamic mapping methods focused on mitigating the negative influence of short-term dynamic objects on camera motion estimation by masking or tracking specific categories, which often fall short in adapting to l

Cited by 2SourceScholar
2025

DiWA: Diffusion Policy Adaptation with World Models

CoRL 2025poster

Fine-tuning diffusion policies with reinforcement learning (RL) presents significant challenges. The long denoising sequence for each action prediction impedes effective reward propagation. Additionally, standard RL methods require millions of physical interaction steps, making fine-tuning even more…

Cited by 0SourceScholar
2024

Hierarchical Open-Vocabulary 3D Scene Graphs for Language-Grounded Robot Navigation

RSS 2024poster

Recent open-vocabulary robot mapping methods enrich dense geometric maps with pre-trained visual-language features. While these maps allow for the prediction of point-wise saliency maps when queried for a certain language concept, large-scale environments and abstract queries beyond the object level…

2024

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

ICRA 2024

Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for man

Cited by 910SourcecodeScholar
2024

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

ICRA 2024poster

Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for man…

Cited by 259SourcecodeScholar