RoboTwin-Platform/RoboTwin

Health v2 · maintenance only

Adoption not part of the score

2772 stars · 466 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

RoboTwin 2.0 is a scalable benchmark and data-generation platform for bimanual (dual-arm) robotic manipulation, built on simulated digital twins with structured domain randomization. It includes an object library of 731 instances, an MLLM-driven expert data synthesis pipeline, and unified evaluation protocols with a public leaderboard.

Use cases

• benchmark dual-arm robot manipulation policies
• generate large-scale synthetic training data for robot learning
• evaluate sim-to-real transfer of manipulation policies
• run domain-randomized simulation experiments for embodied AI
• compare robot policy performance on a public leaderboard

When to choose

• you need a standardized benchmark for bimanual manipulation
• you want automated large-scale synthetic robot data with domain randomization
• you are doing embodied AI / robot learning research and need reproducible evaluation

When to avoid

• you need a single-arm-only or non-manipulation robotics benchmark
• you need a production robot control stack rather than a research benchmark
• you cannot run GPU-accelerated simulation locally

Facets

framework · maturity active

simulation benchmarking data-generation machine-learning robotics robotics artificial-intelligence simulation machine-learning python embodied-ai bimanual-manipulation domain-randomization sim-to-real digital-twin benchmark mllm dataset-generation linux gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="RoboTwin-Platform/RoboTwin")