5 papers · 1 filter
Enhancing Diffusion Policy with Classifier-Free Guidance for Temporal Robotic Tasks
Yuang Lu, Song Wang, Xiao Han +3
Temporal sequential tasks challenge humanoid robots, as existing Diffusion Policy (DP) and Action Chunking with Transformers (ACT) methods often lack temporal context, resulting in…
Manipulation as in Simulation: Enabling Accurate Geometry Perception in Robots
Minghuan Liu, Zhengbang Zhu, Xiaoshen Han +12
Modern robotic manipulation primarily relies on visual observations in a 2D color space for skill learning but suffers from poor generalization. In contrast, humans, living in a 3D…
DAWM: Diffusion Action World Models for Offline Reinforcement Learning via Action-Inferred Transitions
Zongyue Li, Xiao Han, Yusong Li +2
Diffusion-based world models have demonstrated strong capabilities in synthesizing realistic long-horizon trajectories for offline reinforcement learning (RL). However, many existi…
RoboGround: Robotic Manipulation with Grounded Vision-Language Priors
Haifeng Huang, Xinyi Chen, Yilun Chen +6
Recent advancements in robotic manipulation have highlighted the potential of intermediate representations for improving policy generalization. In this work, we explore grounding m…
ReSim: Generating High-Fidelity Simulation Data via 3D-Photorealistic Real-to-Sim for Robotic Manipulation
Xiaoshen Han, Junqiu Yu, Minghuan Liu +6
Real-world data collection for robotics is costly and resource-intensive, requiring skilled operators and expensive hardware. Simulations offer a scalable alternative but often fai…