docs: reorganize Go2 platform docs + map framing default

dimos/mapping/utils/cli/map.py

@@ -97,16 +97,16 @@ def _accumulate(
     block_count: int,
     device: str,
     graph: PoseGraph | None = None,
-    world_frame: bool = False,
+    world_frame: bool = True,
     carve_columns: bool = False,
     progress_cb: Callable[[Observation[Any]], None] | None = None,
 ) -> PointCloud2 | None:
     """Accumulate a voxel map from `obs_iter`, optionally PGO-correcting each frame.
 
-    By default each frame's per-frame pose is applied to register the (sensor/body
-    frame) cloud into the world. Set ``world_frame=True`` (the ``--go2`` path) when
-    the clouds are already world-registered (e.g. fastlio) — then only the PGO
-    correction is applied, if any.
+    By default the clouds are assumed already world-registered (the go2/fastlio
+    path) — only the PGO correction is applied, if any. Set ``world_frame=False``
+    (the ``--use-tf`` path) when each frame's cloud is in the sensor/body frame
+    and must be registered into the world via its per-frame pose.
 
     Returns the final ``PointCloud2`` (or ``None`` if the input was empty).
     Disposal of the underlying ``VoxelGrid`` is handled by ``VoxelMapTransformer``.
@@ -133,7 +133,7 @@ def prepared() -> Iterable[Observation[PointCloud2]]:
             if len(obs.data) == 0:
                 continue
             # body->world via the per-frame pose, unless the clouds are already
-            # world-registered (--go2). graph adds the PGO correction on top
+            # world-registered (go2 default). graph adds the PGO correction on top
             # (correction ∘ pose), applied after the pose.
             tf: Transform | None = None
             if not world_frame:
@@ -328,11 +328,11 @@ def main(
         None, "--out", help="Output .rrd path (default: ./<dataset>.rrd)"
     ),
     no_gui: bool = typer.Option(False, "--no-gui", help="Write the .rrd but don't launch rerun"),
-    go2: bool = typer.Option(
+    use_tf: bool = typer.Option(
         False,
-        "--go2",
-        help="Clouds are already world-registered (e.g. fastlio); skip applying the "
-        "per-frame pose. Default registers each (body-frame) cloud by its pose.",
+        "--use-tf",
+        help="Clouds are in the sensor/body frame; register each by its per-frame pose. "
+        "By default clouds are assumed already world-registered (e.g. go2/fastlio).",
     ),
     carve: bool = typer.Option(
         False,
@@ -470,7 +470,7 @@ def main(
             block_count=block_count,
             device=device,
             graph=graph,
-            world_frame=go2,
+            world_frame=not use_tf,
             carve_columns=carve,
             progress_cb=progress(n_kept, "pgo pass 2 (rebuilding)"),
         )
@@ -484,7 +484,7 @@ def main(
             block_count=block_count,
             device=device,
             graph=graph,
-            world_frame=go2,
+            world_frame=not use_tf,
             carve_columns=carve,
             progress_cb=progress(total, "full pgo (rebuilding)"),
         )
@@ -495,7 +495,7 @@ def main(
         voxel=voxel,
         block_count=block_count,
         device=device,
-        world_frame=go2,
+        world_frame=not use_tf,
         carve_columns=carve,
         progress_cb=progress(n_kept, "reconstructing global map"),
     )

dimos/robot/unitree/go2/blueprints/smart/unitree_go2.py

@@ -21,7 +21,8 @@
 from dimos.mapping.costmapper import CostMapper
 from dimos.mapping.relocalization.module import RelocalizationModule
 from dimos.mapping.voxels import VoxelGridMapper
-from dimos.memory2.module import Recorder, RecorderConfig
+from dimos.memory2.module import Recorder, RecorderConfig, pose_setter_for
+from dimos.msgs.geometry_msgs.Pose import Pose
 from dimos.msgs.geometry_msgs.PoseStamped import PoseStamped
 from dimos.msgs.sensor_msgs.Image import Image
 from dimos.msgs.sensor_msgs.PointCloud2 import PointCloud2
@@ -58,6 +59,17 @@ class Go2Memory(Recorder):
     odom: In[PoseStamped]
     config: Go2MemoryConfig
 
+    _last_odom_pose: Pose | None = None
+
+    @pose_setter_for("odom")
+    def _odom_pose(self, msg: PoseStamped) -> Pose | None:
+        self._last_odom_pose = msg
+        return self._last_odom_pose
+
+    @pose_setter_for("lidar")
+    def _lidar_pose(self, msg: PointCloud2) -> Pose | None:
+        return self._last_odom_pose  # should always exist (odom alwyas wins the race)
+
 
 unitree_go2_markers = (
     autoconnect(

docs/docs.json

@@ -136,7 +136,15 @@
           {
             "group": "Quadruped",
             "pages": [
-              "platforms/quadruped/go2/index"
+              {
+                "group": "Unitree Go2",
+                "pages": [
+                  "platforms/quadruped/go2/index",
+                  "platforms/quadruped/go2/setup",
+                  "platforms/quadruped/go2/simulation",
+                  "platforms/quadruped/go2/premap"
+                ]
+              }
             ]
           },
           {

docs/platforms/quadruped/go2/index.md

@@ -1,150 +1,19 @@
-# Unitree Go2 — Getting Started
+# Unitree Go2 Quick Start
 
-The Unitree Go2 is DimOS's primary reference platform. Full autonomous navigation, mapping, and agentic control — no ROS required.
-
-## Requirements
-
-- Unitree Go2 Pro or Air (stock firmware 1.1.7+, no jailbreak needed)
-- Ubuntu 22.04/24.04 with CUDA GPU (recommended), or macOS (experimental)
-- Python 3.12
-
-## Install
-
-First, install system dependencies for your platform:
-- [Ubuntu](/docs/installation/ubuntu.md)
-- [macOS](/docs/installation/osx.md)
-- [Nix](/docs/installation/nix.md)
-
-Then install DimOS:
-
-```bash
-uv venv --python "3.12"
-source .venv/bin/activate
-uv pip install 'dimos[base,unitree]'
-```
-
-## Try It — No Hardware Needed
-
-```bash
-# Replay a recorded Go2 navigation session
-# First run downloads ~2.4 GB of LiDAR/video data from LFS
-dimos --replay run unitree-go2
-```
-
-Opens the command center at [localhost:7779](http://localhost:7779) with Rerun 3D visualization — watch the Go2 map and navigate an office in real time.
-
-## Run on Your Go2
-
-### First-time setup, connecting to wifi, finding robot IP
-
-Use `dimos go2tool` to provision wifi and find the robot's IP. Skip if the robot is already on your network and you know its IP.
-
-1. Power on the Go2 — it advertises over BLE immediately.
-
-2. Provision wifi (one-time per network):
-
-optionally use discover to make sure robot is detected
-
-```bash
-dimos go2tool discover
-```
-
-configure wifi
-
-```bash
-dimos go2tool connect-wifi --ssid <wifi> --password <password>
-```
-
-Scans BLE and connects to the only robot it finds, or prompts you to pick if there are several.
-
-3. Find the robot's IP:
-
-```bash
-dimos go2tool discover
-```
-
-Prints `SOURCE NAME IP MAC SERIAL` for every robot it sees over BLE and LAN. Export the IP:
-
-```bash
-export ROBOT_IP=<discovered_ip>
-```
-
-### Pre-flight checks
-
-1. Robot is reachable and low latency `<10ms`, 0% packet loss
-```bash
-ping $ROBOT_IP
-```
-
-2. Built-in obstacle avoidance is on. (DimOS handles path planning, but the onboard obstacle avoidance provides an extra safety layer around tight spots)
-
-### Ready to run DimOS
-
-```bash
-export ROBOT_IP=<YOUR_GO2_IP>
-dimos run unitree-go2
-```
-
-That's it. DimOS connects via WebRTC (no jailbreak required), starts the full navigation stack, and opens the command center in your browser.
-
-### What's Running
-
-| Module | What It Does |
-|--------|-------------|
-| **GO2Connection** | WebRTC connection to the robot — streams LiDAR, video, odometry |
-| **VoxelGridMapper** | Builds a 3D voxel map using column-carving (CUDA accelerated) |
-| **CostMapper** | Converts 3D map → 2D costmap via terrain slope analysis |
-| **ReplanningAStarPlanner** | Continuous A* path planning with dynamic replanning |
-| **WavefrontFrontierExplorer** | Autonomous exploration of unmapped areas |
-| **RerunBridge** | 3D visualization in browser |
-| **WebsocketVis** | Command center at localhost:7779 |
-
-### Send Goals
-
-From the command center ([localhost:7779](http://localhost:7779)):
-- Click on the map to set navigation goals
-- Toggle autonomous exploration
-- Monitor robot pose, costmap, and planned path
-
-## MuJoCo Simulation
-
-```bash
-uv pip install 'dimos[base,unitree,sim]'
-dimos --simulation run unitree-go2
-```
-
-Full navigation stack in MuJoCo — same code, simulated robot.
-
-## Agentic Control
-
-Natural language control with an LLM agent that understands physical space:
-
-```bash
-export OPENAI_API_KEY=<YOUR_KEY>
-export ROBOT_IP=<YOUR_GO2_IP>
-dimos run unitree-go2-agentic
-```
-
-Then use the human CLI to talk to the agent:
-
-```bash
-humancli
-> explore the space
-```
-
-The agent subscribes to camera, LiDAR, and spatial memory streams — it sees what the robot sees.
+- [Setup your Dog](/docs/platforms/quadruped/go2/setup.md) — requirements, install, connecting to your Go2, and agentic control
+- [Simulation](/docs/platforms/quadruped/go2/simulation.md) — try it with no hardware via replay or MuJoCo
+- [Record & Load Maps](/docs/platforms/quadruped/go2/premap.md) — record a run, export a premap, and relocalize on replay or a live Go2
 
 ## Available Blueprints
 
 | Blueprint | Description |
 |-----------|-------------|
-| `unitree-go2-basic` | Connection + visualization (no navigation) |
-| `unitree-go2` | Full navigation stack |
-| `unitree-go2-agentic` | Navigation + LLM agent + MCP tool access |
-| `unitree-go2-agentic-ollama` | Agent with local Ollama models |
-| `unitree-go2-spatial` | Navigation + spatial memory |
-| `unitree-go2-detection` | Navigation + object detection |
-| `unitree-go2-ros` | ROS 2 bridge mode |
+| `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 |
 
 ## Deep Dive
 

docs/capabilities/mapping/relocalization.md → docs/platforms/quadruped/go2/premap.md

@@ -1,10 +1,10 @@
-# Relocalization
-
-This walkthrough shows the pre-map capabilities, including how to record,
-export a premap from a mem2 `.db`, and run the robot with relocalization
-enabled. You can also navigate to a place the robot hasn't visited during
-this run, as long as it's part of the global map.
+# Creating a Map
 
+Main steps:
+1. `dimos run unitree-go2-memory` to create a .db file
+2. Auto-clean the .db file into a usable map
+3. Load the map back (replay)
+4. Load the map into the Go2 (live)
 
 ![relocalize on the live go2 and nav_to a point in the premap](assets/reloc_and_nav_to.webp)
 
@@ -15,6 +15,7 @@ this run, as long as it's part of the global map.
 dimos --robot-ip {YOUR_ROBOT_IP} run unitree-go2-memory
 ```
 
+
 If `DIMOS_ROBOT_IP` is set in your environment (or `.env`), you can drop
 the `--robot-ip` flag:
 
@@ -27,16 +28,16 @@ from the repo root so the bare-name lookup finds this file. In the next
 steps `{DB_NAME}` refers to the stem of your recording - `recording_go2`
 if you kept the default.
 
-## 2. Export the premap
+## 2. Auto-clean the .db, convert into a Map
 
-Convert the recording to a relocalization premap (`.pc2.lcm`):
+To create the map file (`.pc2.lcm`):
 
 ```bash
 # default name from step 1:
-dimos map recording_go2 --export
+dimos map global recording_go2 --export
 
 # renamed:
-dimos map {DB_NAME} --export
+dimos map global {DB_NAME} --export
 ```
 
 `--export` implies `--pgo` (runs pose graph optimization) and writes
@@ -53,10 +54,10 @@ When a bare file name is given, the tool searches in:
 Examples:
 
 ```bash
-dimos map go2_hongkong_office --export
-dimos map ./go2_hongkong_office.db --export
-dimos map data/go2_hongkong_office.db --export
-dimos map /abs/path/to/scan.db --export
+dimos map global go2_hongkong_office --export
+dimos map global ./go2_hongkong_office.db --export
+dimos map global data/go2_hongkong_office.db --export
+dimos map global /abs/path/to/scan.db --export
 ```
 
 Sample log: