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cs.RO2026

Decoupling Semantics and Geometric Grounding: Spatial Visual Prompts for Language-Conditioned Imitation Learning

Yanzhe Tang, Xinyu Shao, Yuxuan Hu +6

While end-to-end Vision-Language-Action (VLA) models show promise in robotic manipulation, their monolithic paradigm inherently couples semantic reasoning and spatial control. This…

cs.RO2026

ATG-MoE: Autoregressive trajectory generation with mixture-of-experts for assembly skill learning

Weihang Huang, Chaoran Zhang, Xiaoxin Deng +4

Flexible manufacturing requires robot systems that can adapt to constantly changing tasks, objects, and environments. However, traditional robot programming is labor-intensive and…

cs.RO2026

AssemMate: Graph-Based LLM for Robotic Assembly Assistance

Qi Zheng, Chaoran Zhang, Zijian Liang +5

Large Language Model (LLM)-based robotic assembly assistance has gained significant research attention. It requires the injection of domain-specific knowledge to guide the assembly…

cs.RO2025

More than A Point: Capturing Uncertainty with Adaptive Affordance Heatmaps for Spatial Grounding in Robotic Tasks

Xinyu Shao, Yanzhe Tang, Pengwei Xie +6

Many language-guided robotic systems rely on collapsing spatial reasoning into discrete points, making them brittle to perceptual noise and semantic ambiguity. To address this chal…

cs.RO2025

Demonstrating DVS: Dynamic Virtual-Real Simulation Platform for Mobile Robotic Tasks

Zijie Zheng, Zeshun Li, Yunpeng Wang +2

With the development of embodied artificial intelligence, robotic research has increasingly focused on complex tasks. Existing simulation platforms, however, are often limited to i…