3 citations · 8 across the 15 of their papers we have counts for
13 papers · 1 filter
ForceFlow: Learning to Feel and Act via Contact-Driven Flow Matching
Shuoheng Zhang, Yifu Yuan, Hongyao Tang +7
Existing imitation learning methods enable robots to interact autonomously with the physical environment. However, contact-rich manipulation tasks remain a significant challenge du…
Hybrid Consistency Policy: Decoupling Multi-Modal Diversity and Real-Time Efficiency in Robotic Manipulation
Qianyou Zhao, Yuliang Shen, Xuanran Zhai +5
In visuomotor policy learning, diffusion-based imitation learning has become widely adopted for its ability to capture diverse behaviors. However, approaches built on ordinary and…
ArtGS:3D Gaussian Splatting for Interactive Visual-Physical Modeling and Manipulation of Articulated Objects
Qiaojun Yu, Xibin Yuan, Yu jiang +8
Articulated object manipulation remains a critical challenge in robotics due to the complex kinematic constraints and the limited physical reasoning of existing methods. In this wo…
Noise Fusion-based Distillation Learning for Anomaly Detection in Complex Industrial Environments
Jiawen Yu, Jieji Ren, Yang Chang +7
Anomaly detection and localization in automated industrial manufacturing can significantly enhance production efficiency and product quality. Existing methods are capable of detect…
ForceVLA: Enhancing VLA Models with a Force-aware MoE for Contact-rich Manipulation
Jiawen Yu, Hairuo Liu, Qiaojun Yu +9
Vision-Language-Action (VLA) models have advanced general-purpose robotic manipulation by leveraging pretrained visual and linguistic representations. However, they struggle with c…
SKT: Integrating State-Aware Keypoint Trajectories with Vision-Language Models for Robotic Garment Manipulation
Xin Li, Siyuan Huang, Qiaojun Yu +6
Automating garment manipulation poses a significant challenge for assistive robotics due to the diverse and deformable nature of garments. Traditional approaches typically require…
UniAff: A Unified Representation of Affordances for Tool Usage and Articulation with Vision-Language Models
Qiaojun Yu, Siyuan Huang, Xibin Yuan +9
Previous studies on robotic manipulation are based on a limited understanding of the underlying 3D motion constraints and affordances. To address these challenges, we propose a com…
Articulated Object Manipulation using Online Axis Estimation with SAM2-Based Tracking
Xi Wang, Tianxing Chen, Qiaojun Yu +7
Articulated object manipulation requires precise object interaction, where the object's axis must be carefully considered. Previous research employed interactive perception for man…
ManiPose: A Comprehensive Benchmark for Pose-aware Object Manipulation in Robotics
Qiaojun Yu, Ce Hao, Junbo Wang +6
Robotic manipulation in everyday scenarios, especially in unstructured environments, requires skills in pose-aware object manipulation (POM), which adapts robots' grasping and hand…
RPMArt: Towards Robust Perception and Manipulation for Articulated Objects
Junbo Wang, Wenhai Liu, Qiaojun Yu +4
Articulated objects are commonly found in daily life. It is essential that robots can exhibit robust perception and manipulation skills for articulated objects in real-world roboti…
GAMMA: Generalizable Articulation Modeling and Manipulation for Articulated Objects
Qiaojun Yu, Junbo Wang, Wenhai Liu +5
Articulated objects like cabinets and doors are widespread in daily life. However, directly manipulating 3D articulated objects is challenging because they have diverse geometrical…
ClothesNet: An Information-Rich 3D Garment Model Repository with Simulated Clothes Environment
Bingyang Zhou, Haoyu Zhou, Tianhai Liang +10
We present ClothesNet: a large-scale dataset of 3D clothes objects with information-rich annotations. Our dataset consists of around 4400 models covering 11 categories annotated wi…
SAGCI-System: Towards Sample-Efficient, Generalizable, Compositional, and Incremental Robot Learning
Jun Lv, Qiaojun Yu, Lin Shao +3
Building general-purpose robots to perform a diverse range of tasks in a large variety of environments in the physical world at the human level is extremely challenging. It require…