4 papers
FD-VLA: Force-Distilled Vision-Language-Action Model for Contact-Rich Manipulation
Ruiteng Zhao, Wenshuo Wang, Yicheng Ma +4
Force sensing is a crucial modality for Vision-Language-Action (VLA) frameworks, as it enables fine-grained perception and dexterous manipulation in contact-rich tasks. We present…
Opinion: Towards Unified Expressive Policy Optimization for Robust Robot Learning
Haidong Huang, Haiyue Zhu. Jiayu Song, Xixin Zhao +4
Offline-to-online reinforcement learning (O2O-RL) has emerged as a promising paradigm for safe and efficient robotic policy deployment but suffers from two fundamental challenges:…
A Dual Large Language Models Architecture with Herald Guided Prompts for Parallel Fine Grained Traffic Signal Control
Qing Guo, Xinhang Li, Junyu Chen +4
Leveraging large language models (LLMs) in traffic signal control (TSC) improves optimization efficiency and interpretability compared to traditional reinforcement learning (RL) me…
Robotic Control Optimization Through Kernel Selection in Safe Bayesian Optimization
Lihao Zheng, Hongxuan Wang, Xiaocong Li +2
Control system optimization has long been a fundamental challenge in robotics. While recent advancements have led to the development of control algorithms that leverage learning-ba…