4 citations · 4 across the 10 of their papers we have counts for
6 papers · 1 filter
Robotic Ultra-Long-Horizon Manipulation Skills via Human-guided Lifelong Code Generation
Yuan Meng, Zhenguo Sun, Max Fest +4
Large language models (LLMs) can translate natural-language instructions for robotic manipulation into executable code, but ambiguity, noisy generations, and limited context window…
Inference-stage Adaptation-projection Strategy Adapts Diffusion Policy to Cross-manipulators Scenarios
Xiangtong Yao, Yirui Zhou, Yuan Meng +7
Diffusion policies are powerful visuomotor models for robotic manipulation, yet they often fail to generalize to manipulators or end-effectors unseen during training and struggle t…
RobotDancing: Residual-Action Reinforcement Learning Enables Robust Long-Horizon Humanoid Motion Tracking
Zhenguo Sun, Yibo Peng, Yuan Meng +5
Long-horizon, high-dynamic motion tracking on humanoids remains brittle: retargeted reference motions are typically kinematically plausible but dynamically inconsistent with the ro…
Robotic Long-Horizon Manipulation with Bayesian Non-parametric Skill Priors
Yuan Meng, Xiangtong Yao, Kejia Chen +5
Long-horizon manipulation under sparse rewards remains challenging for reinforcement learning due to delayed feedback and inefficient exploration. Existing skill-based approaches o…
Robotic Long-Horizon Manipulation with Progressive In-Context Code Generation and Episodic Feedback
Yuan Meng, Xiangtong Yao, Haihui Ye +6
Robotic long-horizon manipulation requires robots to compose perception, reasoning, and action over extended task sequences, yet existing language-conditioned frameworks often rely…
Pick-and-place Manipulation Across Grippers Without Retraining: A Learning-optimization Diffusion Policy Approach
Xiangtong Yao, Yirui Zhou, Yuan Meng +7
Current robotic pick-and-place policies typically require consistent gripper configurations across training and inference. This constraint imposes high retraining or fine-tuning co…