3 papers
cs.AI2025
MCTS-EP: Empowering Embodied Planning with Online Preference Optimization
Hang Xu, Zang Yu, Yehui Tang +3
This paper introduces MCTS-EP, an online learning framework that combines large language models (LLM) with Monte Carlo Tree Search (MCTS) for training embodied agents. MCTS-EP inte…
cs.RO2025
Towards Proprioception-Aware Embodied Planning for Dual-Arm Humanoid Robots
Boyu Li, Siyuan He, Hang Xu +10
In recent years, Multimodal Large Language Models (MLLMs) have demonstrated the ability to serve as high-level planners, enabling robots to follow complex human instructions. Howev…
cs.RO2025
DualTHOR: A Dual-Arm Humanoid Simulation Platform for Contingency-Aware Planning
Boyu Li, Siyuan He, Hang Xu +9
Developing embodied agents capable of performing complex interactive tasks in real-world scenarios remains a fundamental challenge in embodied AI. Although recent advances in simul…