Researchers introduced FurnitureVLA, a Vision-Language-Action model for learning real-scale bimanual furniture assembly, submitted to arXiv on July 1, 2026, marking the first systematic study of its kind.
The system handles extreme long-horizon tasks with up to 7 subtasks and 1,550 control steps, improving simulation success from 48% to 80% compared to baseline models.
The approach combines a progress-enhanced VLA that jointly predicts actions and continuous progress signals for automatic subtask transitions, complemented by a VR teleoperation system for collecting high-quality real-world demonstrations.