// the find
simpler-env/SimplerEnv
Evaluating and reproducing real-world robot manipulation policies (e.g., RT-1, RT-1-X, Octo) in simulation under common setups (e.g., Google Robot, WidowX+Bridge) (CoRL 2024)
SimplerEnv is a simulation benchmark for evaluating generalist robot manipulation policies (RT-1, RT-1-X, Octo) against real Google Robot and WidowX+Bridge setups, so you can rank checkpoints without burning real robot time. It's built for robot learning researchers who need reproducible, cheap policy evaluation as a proxy for real-world rollouts.
It ships two distinct evaluation methodologies (visual matching via real-image overlay, and variant aggregation across backgrounds/lighting/distractors) plus published metrics (MMRV, Pearson correlation) that quantify how well the sim results track real robot performance, not just a black-box simulator. It comes with real-world performance numbers for RT-1, RT-1-X, and Octo baked in, so you can directly compare a new evaluation approach against ground truth using the provided REAL_PERF data and metrics.py. The API is a one-liner (simpler_env.make(...)) with prepackaged environments and a Colab notebook, so you get usable pixels and rewards before touching SAPIEN or ManiSkill internals. The ManiSkill3 branch adds GPU parallelization for the Bridge environments at a claimed 10-15x speedup over the CPU-based ManiSkill2 path.
The full install is a multi-hour ordeal: CUDA pinned to 11.8-13, numpy<2.0 to avoid IK breakage in pinocchio, a specific git submodule commit for Octo, and separate tensorflow/jax stacks depending on whether you're running RT-1 or Octo. SAPIEN's Vulkan rendering is flaky enough to warrant its own troubleshooting section, and non-RTX GPUs (1080Ti, A100) are explicitly called out as slow for ray-traced environments. Coverage is narrow out of the box — 4 robot embodiments, 10 base tasks — and adding a new robot or environment means system identification and asset creation work spelled out in a separate README, not a same-day task. The GPU-parallelized ManiSkill3 path lives on a different branch entirely, so the main branch you land on is already partially legacy and the docs split attention between two simulator generations.