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Bryan Ribas edited this page Jul 31, 2026
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Experimenting with Vision-Language-Action policies on a Universal Robots UR5e (with an AmazingHand end-effector), using LeRobot. Simulation-first; real-hardware teleop + recording works (datasets captured on the robot). RTDE drives the arm for teleop; ROS 2 is reserved for autonomous deployment.
See ROADMAP.md for the full plan and docs/decisions.md for open architectural choices.
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Machines & Network — the three machines, the isolated robot subnet, and
run.shon the robot PC. - Hardware Teleop & Recording — the RTDE teleop panel, cameras, Stream Deck, home pose, auto-upload + star rating + auto-home-on-save.
- Recording Sim Demos — MuJoCo teleop capture and the sim grasp aid.
- Training & Eval — train ACT / fine-tune SmolVLA, sim eval, playback, merge/recover.
- Web Manager (RobotDisco) — the browser console for datasets · models · evals (native or Docker).
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Deploy on Hardware — run a trained policy on the real UR5e (
eval_hw.py), Stream-Deck driven. - 8-DOF Hand — per-finger flex + abduct (in progress).
- Sync & Layout — moving code between machines and the repo map.