6 papers · 1 filter
OneDemo: Unified Policy Learning and Data Generation from a Single Demonstration
Ying Qian, Jianshu Hu, Han Fang +2
Learning robot policies from demonstrations is often limited by the cost of collecting diverse, high-quality expert data. While an appealing alternative is to expand a single succe…
RESTA: Time-Scaling Augmentation for Data-Efficient Robot Imitation Learning
Yunpeng Jiang, Jianshu Hu, Han Fang +3
Robot manipulation policies trained through imitation learning commonly rely on costly demonstrations recorded in one task direction and at one temporal resolution. We propose Reve…
LEAP: Making Privileged Geometry Supervision Effective for Visuomotor Learning
Han Fang, Yunpeng Jiang, Jianshu Hu +6
Privileged 3D supervision uses additional geometric information during training to guide RGB-based visuomotor policy learning, without requiring geometric inputs at deployment. How…
DSSP: Diffusion State Space Policy with Full-History Encoding
Zhiyuan Guan, Jianshu Hu, Han Fang +5
Diffusion-based imitation learning has shown strong promise for robot manipulation. However, most existing policies condition only on the current observation or a short window of r…
OMP: One-step Meanflow Policy with Directional Alignment
Han Fang, Yize Huang, Yuheng Zhao +3
Robot manipulation has increasingly adopted data-driven generative policy frameworks, yet the field faces a persistent trade-off: diffusion models suffer from high inference latenc…
Time Reversal Symmetry for Efficient Robotic Manipulations in Deep Reinforcement Learning
Yunpeng Jiang, Jianshu Hu, Paul Weng +1
Symmetry is pervasive in robotics and has been widely exploited to improve sample efficiency in deep reinforcement learning (DRL). However, existing approaches primarily focus on s…