5 papers · 1 filter
ALAS: Adaptive Long-Horizon Action Synthesis via Async-pathway Stream Disentanglement
Yutong Shen, Hangxu Liu, Lei Zhang +4
Long-Horizon (LH) tasks in Human-Scene Interaction (HSI) are complex multi-step tasks that require continuous planning, sequential decision-making, and extended execution across do…
MetaWorld-X: Hierarchical World Modeling via VLM-Orchestrated Experts for Humanoid Loco-Manipulation
Yutong Shen, Hangxu Liu, Penghui Liu +6
Learning natural, stable, and compositionally generalizable whole-body control policies for humanoid robots performing simultaneous locomotion and manipulation (loco-manipulation)…
MetaWorld: Skill Transfer and Composition in a Hierarchical World Model for Grounding High-Level Instructions
Yutong Shen, Hangxu Liu, Kailin Pei +2
Humanoid robot loco-manipulation remains constrained by the semantic-physical gap. Current methods face three limitations: Low sample efficiency in reinforcement learning, poor gen…
DETACH: Cross-domain Learning for Long-Horizon Tasks via Mixture of Disentangled Experts
Yutong Shen, Hangxu Liu, Lei Zhang +4
Long-Horizon (LH) tasks in Human-Scene Interaction (HSI) are complex multi-step tasks that require continuous planning, sequential decision-making, and extended execution across do…
GundamQ: Multi-Scale Spatio-Temporal Representation Learning for Robust Robot Path Planning
Yutong Shen, Ruizhe Xia, Bokai Yan +4
In dynamic and uncertain environments, robotic path planning demands accurate spatiotemporal environment understanding combined with robust decision-making under partial observabil…