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Embodied AI · Robot control · Learn by doing

Meet MayaGo.
Make intelligence move.

An original, self-hosted 3D robot lab. Drive, turn, test recovery and switch between walking legs and wheels—all inside your browser, without an external simulator.

SELF-HOSTED 3DKEYBOARD + TOUCHUGANDA MISSIONS
MAI
SenseActLearn
MayaGo Simulation DeckLocal 3D renderer · interactive motion sandbox
3D ENGINE READYMODE · WALKINGPOSE · STANDING
SPEED0.00 m/s*
HEADING000°
CONTROLIDLE
STABILITYSTABLE
MAYAGO / TRAINING ARENA SIMULATED WORLD
Welcome to MayaGo. Use WASD or the control pad to move.
MOVEMENT

WASD / Arrow keys

ROBOT ACTIONS
LIVE TELEMETRY
Forward command
Turn command
Gait phase

*Illustrative speed estimate. This learning build uses a custom kinematic motion model, not the original trained policy.

Camera: drag to orbit · scroll to zoom · Space resets · M switches legs/wheelsReady · running locally in your browser
Uganda missions

Learn with a purpose.

Test a behaviour, record what your team learned, and identify what needs proper physics or real-world validation.

Mission 01 · Mobility

Navigate a busy school corridor

Explore how turning speed and obstacle distance affect navigation. This sandbox does not model human collision risk.

Mission 02 · Resilience

Recover after losing balance

Trigger the recovery sequence, repeat it and note its limits. An animated recovery is not proof of real-world reliability.

Mission 03 · Community

Plan a water-point inspection

Design a route and list the measurements, sensors and human checks needed for a useful inspection.

Mission notebook

Turn an experiment into evidence.

Notes are saved in this browser. Sign in to submit a shareable idea to the Grid.

AI field guide

Think like a robotics engineer.

  1. Observe: record what the robot actually did.
  2. Hypothesise: change one factor at a time.
  3. Measure: compare repeatable outcomes.
  4. Protect: define stop conditions and human oversight.
  5. Validate: real robot deployment requires real physics, trained policies and safety testing.
This version is a self-hosted 3D learning sandbox. It does not yet include MuJoCo WASM physics or the original ONNX policy weights.
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