8 papers
PRISM: Precision Forcing for Generalist Vision-Language-Action Policies
Chenghao Yue, Peiyan Li, Hao Wang +5
Coupling a pretrained vision-language model (VLM) with a diffusion or flow-matching action expert has become the mainstream vision-language-action (VLA) paradigm for embodied polic…
TimelyDAgger: Timing-Aware Expert Querying for VLA Policy Improvement
Zhixuan Zhao, Peiyan Li, Enhao Zhang +10
DAgger improves robot policies by aggregating expert supervision from states visited during policy execution. Robot-gated DAgger automates expert queries, allowing the robot to dec…
Beyond State-as-Action: Exploiting Command-State Discrepancy for Robot Imitation Learning
Peiyan Li, Yueran Tao, Enhao Zhang +10
Constructing action targets from measured robot motion is an established approach in imitation learning. Under interaction constraints, however, command-state discrepancy may refle…
Ratio-Variance Regularized Policy Optimization
Yu Luo, Shuo Han, Yihan Hu +5
Standard on-policy reinforcement learning relies on heuristic clipping to enforce trust regions, but this mechanism imposes a severe cost by indiscriminately truncating high-return…
Periodic Steady-State Control of a Handkerchief-Spinning Task Using a Parallel Anti-Parallelogram Tendon-driven Wrist
Lei Liu, Haonan Zhang, Huahang Xu +8
Spinning flexible objects, exemplified by traditional Chinese handkerchief performances, demands periodic steady-state motions under nonlinear dynamics with frictional contacts and…
FLAC: Maximum Entropy RL via Kinetic Energy Regularized Bridge Matching
Lei Lv, Yunfei Li, Yu Luo +2
Iterative generative policies, such as diffusion models and flow matching, offer superior expressivity for continuous control but complicate Maximum Entropy Reinforcement Learning…
Flow-Based Policy for Online Reinforcement Learning
Lei Lv, Yunfei Li, Yu Luo +4
We present \textbf{FlowRL}, a novel framework for online reinforcement learning that integrates flow-based policy representation with Wasserstein-2-regularized optimization. We arg…
Multi-segment Soft Robot Control via Deep Koopman-based Model Predictive Control
Lei Lv, Lei Liu, Lei Bao +7
Soft robots, compared to regular rigid robots, as their multiple segments with soft materials bring flexibility and compliance, have the advantages of safe interaction and dexterou…