- Setup your Dog: requirements, install, connecting to your Go2, and agentic control
- Simulation: try it with no hardware via replay or MuJoCo
- Mapping & Navigation: live nav, premap recording, and relocalization
| Blueprint | Description |
|---|---|
dimos run unitree-go2-basic |
Connection + visualization (no navigation) |
dimos run unitree-go2 |
Full navigation stack |
dimos run unitree-go2-agentic |
Navigation + LLM agent + MCP tool access |
dimos run unitree-go2-agentic-ollama |
Agent with local Ollama models |
dimos run unitree-go2-spatial |
Navigation + spatial memory |
dimos run unitree-go2-detection |
Navigation + object detection |
dimos --record run unitree-go2 |
Navigation + record every stream to recordings/<run-id>/memory.db (Recording) |
dimos run unitree-go2-memory |
Navigation + record lidar/odom/color_image to .db |
dimos --record run unitree-go2-joystick-record |
Teleop from the local keyboard window + record joystick, cmd_vel and every sensor; no mapper, viewer capped at 2 GB |
dimos run unitree-go2 --map-file=<map> |
Navigation on a saved map (<map>.map.db) |
dimos run unitree-go2-map |
Navigation on a map that every run extends and saves back (map_go2) |
- Navigation overview: live mapping vs premap relocalization
- Navigation stack: column-carving voxel mapping, costmap generation, A* planning
- Mapping and relocalization: permanent map, relocalizing on a saved map
- Visualization: Rerun, performance tuning
- Data Streams: RxPY streams, backpressure, quality filtering
- Transports: Zenoh, LCM, DDS
- Blueprints: composing modules