6 papers
Learning Robust Execution in Robotic Manipulation with Agentic Reinforcement Learning
Xiaopeng Zhang, Yueyang Weng, Qi Liu +2
Robotic manipulation poses fundamental challenges due to uncertainty, long-horizon execution, and compounding errors, which can easily destabilize execution and lead to task failur…
Temporal Action Selection for Action Chunking
Yueyang Weng, Xiaopeng Zhang, Yongjin Mu +2
Action chunking is a widely adopted approach in Learning from Demonstration (LfD). By modeling multi-step action chunks rather than single-step actions, action chunking significant…
MASH: Cooperative-Heterogeneous Multi-Agent Reinforcement Learning for Single Humanoid Robot Locomotion
Qi Liu, Xiaopeng Zhang, Mingshan Tan +3
This paper proposes a novel method to enhance locomotion for a single humanoid robot through cooperative-heterogeneous multi-agent deep reinforcement learning (MARL). While most ex…
Hierarchical Reinforcement Learning for Safe Mapless Navigation with Congestion Estimation
Jianqi Gao, Xizheng Pang, Qi Liu +1
Reinforcement learning-based mapless navigation holds significant potential. However, it faces challenges in indoor environments with local minima area. This paper introduces a saf…
MASQ: Multi-Agent Reinforcement Learning for Single Quadruped Robot Locomotion
Qi Liu, Jingxiang Guo, Sixu Lin +3
This paper proposes a novel method to improve locomotion learning for a single quadruped robot using multi-agent deep reinforcement learning (MARL). Many existing methods use singl…
Multi-Agent Target Assignment and Path Finding for Intelligent Warehouse: A Cooperative Multi-Agent Deep Reinforcement Learning Perspective
Qi Liu, Jianqi Gao, Dongjie Zhu +4
Multi-agent target assignment and path planning (TAPF) are two key problems in intelligent warehouse. However, most literature only addresses one of these two problems separately.…