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20232026
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cs.RO2026

From Flow to One Step: Real-Time Multi-Modal Trajectory Policies via Implicit Maximum Likelihood Estimation-based Distribution Distillation

Ju Dong, Liding Zhang, Lei Zhang +7

Generative policies based on diffusion and flow matching achieve strong performance in robotic manipulation by modeling multi-modal human demonstrations. However, their reliance on…

cs.RO2026

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)…

cs.RO2025

ResponsibleRobotBench: Benchmarking Responsible Robot Manipulation using Multi-modal Large Language Models

Lei Zhang, Ju Dong, Kaixin Bai +4

Recent advances in large multimodal models have enabled new opportunities in embodied AI, particularly in robotic manipulation. These models have shown strong potential in generali…

cs.RO2025

OmniDexVLG: Learning Dexterous Grasp Generation from Vision Language Model-Guided Grasp Semantics, Taxonomy and Functional Affordance

Lei Zhang, Diwen Zheng, Kaixin Bai +5

Dexterous grasp generation aims to produce grasp poses that align with task requirements and human interpretable grasp semantics. However, achieving semantically controllable dexte…

cs.RO2025

FUNCanon: Learning Pose-Aware Action Primitives via Functional Object Canonicalization for Generalizable Robotic Manipulation

Hongli Xu, Lei Zhang, Xiaoyue Hu +7

General-purpose robotic skills from end-to-end demonstrations often leads to task-specific policies that fail to generalize beyond the training distribution. Therefore, we introduc…

cs.RO2025

M4Diffuser: Multi-View Diffusion Policy with Manipulability-Aware Control for Robust Mobile Manipulation

Ju Dong, Lei Zhang, Liding Zhang +8

Mobile manipulation requires the coordinated control of a mobile base and a robotic arm while simultaneously perceiving both global scene context and fine-grained object details. E…