1 citations · 1 across the 10 of their papers we have counts for
11 papers
SkillMemo: Expert-guided Skill Memory Framework for Compositional Embodied Manipulation
Changyuan Wang, Chubin Zhang, Zhenyu Wu +8
Embodied visuomotor models, including Diffusion Policy (DP) and Vision-Language-Action (VLA) models, have demonstrated promising performance on robotic manipulation benchmarks. How…
BiDexGrasp: Coordinated Bimanual Dexterous Grasps across Object Geometries and Sizes
Mu Lin, Yi-Lin Wei, Jiaxuan Chen +7
Bimanual dexterous grasping is a fundamental and promising area in robotics, yet its progress is constrained by the lack of comprehensive datasets and powerful generation models. I…
Human-in-the-loop Online Rejection Sampling for Robotic Manipulation
Guanxing Lu, Rui Zhao, Haitao Lin +2
Reinforcement learning (RL) is widely used to produce robust robotic manipulation policies, but fine-tuning vision-language-action (VLA) models with RL can be unstable due to inacc…
RESample: A Robust Data Augmentation Framework via Exploratory Sampling for Robotic Manipulation
Yuquan Xue, Guanxing Lu, Zhenyu Wu +4
Vision-Language-Action (VLA) models have shown strong manipulation capability when trained with large-scale imitation learning datasets. However, these datasets that predominantly…
RoDyn: Taming Interactive Robot-Dynamic 2.5D World Model for Robotic Manipulation
Chuanrui Zhang, Zhengxian Wu, Guanxing Lu +2
Learned world models hold significant potential as neural simulators for robotic manipulation. However, prevalent 2D video-based models inherently lack the spatial and kinematic re…
DSPv2: Improved Dense Policy for Effective and Generalizable Whole-body Mobile Manipulation
Yue Su, Chubin Zhang, Sijin Chen +4
Learning whole-body mobile manipulation via imitation is essential for generalizing robotic skills to diverse environments and complex tasks. However, this goal is hindered by sign…
GWM: Towards Scalable Gaussian World Models for Robotic Manipulation
Guanxing Lu, Baoxiong Jia, Puhao Li +4
Training robot policies within a learned world model is trending due to the inefficiency of real-world interactions. The established image-based world models and policies have show…
VLA-Reasoner: Empowering Vision-Language-Action Models with Reasoning via Online Monte Carlo Tree Search
Wenkai Guo, Guanxing Lu, Haoyuan Deng +3
Vision-Language-Action models (VLAs) achieve strong performance in general robotic manipulation tasks by scaling imitation learning. However, existing VLAs are limited to predictin…
ManiGaussian++: General Robotic Bimanual Manipulation with Hierarchical Gaussian World Model
Tengbo Yu, Guanxing Lu, Zaijia Yang +7
Multi-task robotic bimanual manipulation is becoming increasingly popular as it enables sophisticated tasks that require diverse dual-arm collaboration patterns. Compared to uniman…
VLA-RL: Towards Masterful and General Robotic Manipulation with Scalable Reinforcement Learning
Guanxing Lu, Wenkai Guo, Chubin Zhang +5
Recent high-capacity vision-language-action (VLA) models have demonstrated impressive performance on a range of robotic manipulation tasks by imitating human demonstrations. Howeve…
AnyBimanual: Transferring Unimanual Policy for General Bimanual Manipulation
Guanxing Lu, Tengbo Yu, Haoyuan Deng +3
Performing general language-conditioned bimanual manipulation tasks is of great importance for many applications ranging from household service to industrial assembly. However, col…