FurnitureVLA: Learning Long-Horizon Bimanual Furniture Assembly with Vision-Language-Action Model
Current work on robot furniture assembly mostly focuses on toy-scale settings or single-arm manipulation. We introduce FurnitureVLA, the first systematic study of real-scale bimanual furniture assembly using Vision-Language-Action models (VLAs). We formalize the task, develop a scalable simulation pipeline for expert data generation and evaluation, and build a VR teleoperation system for single-operator bimanual control to collect high-quality real-world demonstrations. To address extreme long-horizon assembly with up to 7 subtasks and 1550 control steps, we propose a progress-enhanced VLA, fi
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- LinkedLinked via unknownAgentCore-8B →
- LinkedLinked via unknownVioletVision-3B →
- LinkedLinked via arxiv author · 85%Chenyang Ma →
“FurnitureVLA: Learning Long-Horizon Bimanual Furniture Assembly with Vision-Language-Action Model”
- LinkedLinked via arxiv author · 85%Yue Yang →
“FurnitureVLA: Learning Long-Horizon Bimanual Furniture Assembly with Vision-Language-Action Model”
- LinkedLinked via arxiv author · 85%Radu Corcodel →
“FurnitureVLA: Learning Long-Horizon Bimanual Furniture Assembly with Vision-Language-Action Model”
- LinkedLinked via arxiv author · 85%Siddarth Jain →
“FurnitureVLA: Learning Long-Horizon Bimanual Furniture Assembly with Vision-Language-Action Model”
- LinkedLinked via arxiv author · 85%Andrew Wu →
“FurnitureVLA: Learning Long-Horizon Bimanual Furniture Assembly with Vision-Language-Action Model”
- LinkedLinked via arxiv author · 85%Chiori Hori →
“FurnitureVLA: Learning Long-Horizon Bimanual Furniture Assembly with Vision-Language-Action Model”