simpler-env/SimplerEnv

Health v2 · maintenance only

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1147 stars · 198 forks observed · 2026-08-28

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

SIMPLER (SimplerEnv) is a collection of simulated environments built on SAPIEN/ManiSkill for evaluating real-world robot manipulation policies like RT-1, RT-1-X, and Octo. It provides real-to-sim evaluation setups (Visual Matching and Variant Aggregation) that correlate strongly with real-world robot performance.

Use cases

• evaluate robot manipulation policies in simulation
• reproduce real-world robot policy results without physical robots
• benchmark RT-1 or Octo policies on Google Robot and WidowX setups
• select checkpoints for robot learning models using sim metrics
• study real-to-sim gap for manipulation evaluation
• run scalable reproducible robot policy evaluations

When to choose

• you need to evaluate generalist manipulation policies without expensive real-robot runs
• you want standardized, reproducible robot evaluation setups
• you need sim-based checkpoint selection or failure mode analysis for robot policies

When to avoid

• you need full-fidelity digital twins of specific real environments
• your robot setup or task is not among the supported environments
• you need high-fidelity contact dynamics rather than policy-level evaluation

Facets

framework · maturity active

simulation machine-learning computer-vision benchmarking robotics robotics machine-learning simulation computer-vision artificial-intelligence python robot-manipulation real2sim robot-learning maniskill sapien policy-evaluation benchmark embodied-ai reinforcement-learning linux gpu

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markdown · JSON · MCP: product_card(name="simpler-env/SimplerEnv")