7 papers
WAM-OPD: Joint Video-Action Supervision for World Action Model Post-Training with On-Policy Distillation
Liuhaichen Yang, Zhengyang Zhong, Zhuang Jiang +13
World Action Models (WAMs) generate both future video and robot actions, offering two connected outputs for post-training supervision. How can a pretrained WAM learn from a stronge…
Guided Action Flow: Value-Guided Sampling for Frozen Vision-Language-Action Policies
Liuhaichen Yang, Zhuang Jiang, Chenchao Sheng +8
Reinforcement learning can improve vision-language-action (VLA) policies beyond supervised fine-tuning, although this typically involves further updates to the policy parameters. F…
SignVLA: Real-Time Sign Language-Guided Robotic Manipulation via Attention LSTM and Vision-Language-Action Models
Ningwei Bai, Xinyu Tan, Harry Gardner +6
Vision-Language-Action (VLA) models enable robots to execute manipulation tasks from natural-language instructions grounded in visual observations. However, existing VLA interfaces…
SignVLA: A Gloss-Free Vision-Language-Action Framework for Real-Time Sign Language-Guided Robotic Manipulation
Xinyu Tan, Ningwei Bai, Harry Gardener +6
We present, to our knowledge, the first sign language-driven Vision-Language-Action (VLA) framework for intuitive and inclusive human-robot interaction. Unlike conventional approac…
Disturbance observer-based tracking control for roll-to-roll slot die coating systems under gap and pump rate disturbances
Zezhi Tang, Christopher Passmore, Andrew I Campbell +4
Roll-to-roll slot die coating is a widely used industrial manufacturing technique applied in a diverse range of applications such as the production of lithium-ion batteries, solar…
Deep Reinforcement Learning Optimization for Uncertain Nonlinear Systems via Event-Triggered Robust Adaptive Dynamic Programming
Ningwei Bai, Chi Pui Chan, Qichen Yin +3
This work proposes a unified control architecture that couples a Reinforcement Learning (RL)-driven controller with a disturbance-rejection Extended State Observer (ESO), complemen…
A temporal scale transformer framework for precise remaining useful life prediction in fuel cells
Zezhi Tang, Xiaoyu Chen, Xin Jin +2
In exploring Predictive Health Management (PHM) strategies for Proton Exchange Membrane Fuel Cells (PEMFC), the Transformer model, widely used in data-driven approaches, excels in…