RoboTwin introduces a generative digital twin framework that addresses the critical shortage of demonstration data for dual-arm robotic manipulation tasks.

• Creates diverse expert datasets using 3D generative foundation models and large language models
• Enables high-quality training for complex object manipulation and coordination
• Provides real-world-aligned evaluation benchmarks for autonomous systems
• Bridges the gap between simulation and physical robotic implementation

This research significantly advances industrial robotics by democratizing access to high-quality training data, potentially accelerating development of versatile factory automation systems capable of handling complex manufacturing tasks.

RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins