2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.RO2026
How to Learn from What a Human Would Avoid? Intervention-Aware World Models with Real-World RL for Dexterous Manipulation
Jiaju Yin, Zhenhui Zhang, Lixin Xu +5
Multi-fingered dexterous manipulation remains a frontier for real-world reinforcement learning (RL) due to the high-dimensional action space and the prohibitive cost of hardware fa…
cs.RO2024★ 2 cited
MLDT: Multi-Level Decomposition for Complex Long-Horizon Robotic Task Planning with Open-Source Large Language Model
Yike Wu, Jiatao Zhang, Nan Hu +5
In the realm of data-driven AI technology, the application of open-source large language models (LLMs) in robotic task planning represents a significant milestone. Recent robotic t…