robonix.service.mapping
service
v0.5.0
SLAM mapping service. Algo + sensor inputs config-driven.
mapping_rbnx
SLAM mapping service for Robonix. It
turns a robot's lidar / camera / odom streams into a live 2D occupancy
grid, a 3D point cloud, and a SLAM-corrected pose, published under a
fixed, engine-agnostic capability surface (robonix/service/map/*), and
persists named maps so a robot can re-localize across restarts.
It is a Robonix service package: it registers with atlas, discovers its
sensor inputs by capability contract (never hardcoded topics), and is brought
up by rbnx boot. Consumers (scene, nav) bind the contracts, not the
SLAM engine.
- Capability surface, config schema, and persistence layout: CAPABILITY.md.
- Provider instance configuration reference: config.spec.
SLAM engines (algo)
| algo | use | inputs |
|---|---|---|
rtabmap (default, recommended) |
sim + real; 2D/3D/RGBD, sensor-agnostic | any of lidar2d / lidar3d / rgbd (+ odom) |
dlio |
real-robot 3D Livox + IMU | lidar3d + imu, needs a colcon ws at /ws/install |
fastlio2 |
broken (drift) — repro only | — |
The launch branches on the provider roles bound by the deployment, so the same service supports 2D lidar, 3D lidar, RGB-D, and external odometry without robot-specific branches.
How to integrate it on your robot
- Register your sensors as Robonix primitives under the standard
contracts (
robonix/primitive/lidar/lidar3d,.../camera/depth,.../chassis/odom, …). mapping discovers them via atlas. - Pick a deployment target and reference the matching package manifest
from your deploy
robonix_manifest.yaml:
service:
- name: mapping
url: https://github.com/syswonder/service-map-rbnx
# manifest: package_manifest.jetson-native.yaml # x86+docker is default
config:
sensor_providers:
lidar3d: roof_lidar
rgb: front_camera
depth: front_camera
odom: base_chassis
occupancy_sources: [lidar]
deskew_lidar: true
params_file: config/rtabmap_params.yaml
rtabmap_params:
Grid/FootprintLength: 0.84
Grid/FootprintWidth: 0.60
rbnx build -f robonix_manifest.yaml then rbnx boot -f robonix_manifest.yaml.
4. Consume the map: subscribe to robonix/service/map/occupancy_grid /
.../pointcloud / .../pose (resolve them via atlas).
config/rtabmap_params.template.yaml is
only a starting template. Copy it into the robot deployment repository and set
params_file; Mapping never loads the upstream template at runtime. Inline
rtabmap_params applies after the deploy-owned file.
With external odometry, deskew_lidar compensates each PointCloud2 point in
the odom frame before SLAM. Bind only the sensor roles Mapping should consume.
Separate localization and navigation odometry
Some robots need accurate ICP/RGB-D odometry for RTAB-Map localization but a lower-latency chassis odometry stream for navigation. Enable the optional split-odometry bridge for this setup:
service:
- name: mapping
url: https://github.com/syswonder/service-map-rbnx
config:
algo: rtabmap
base_frame: base_link
# Private RTAB-Map odometry frame.
odom_frame: odom_icp
# Public chassis odometry used by navigation.
navigation_odom_bridge: true
navigation_odom_topic: /odom
navigation_odom_frame: odom
sensor_providers:
lidar3d: roof_lidar
# Do not bind odom in split-odometry mode.
In this mode, RTAB-Map uses an internal message-only odometry trajectory in
odom_icp, the chassis owns odom -> base_link, and Mapping publishes the
correction required by navigation:
map -> odom -> base_link
The bridge computes map -> odom from RTAB-Map localization and the two
timestamp-aligned odometry poses. odom_frame and navigation_odom_frame
must be different, and sensor_providers.odom must not be configured.
The feature defaults to false; existing external- and internal-odometry
deployments are unchanged. See config.spec for the complete
field definitions.
Deployment targets
One package, three targets (selected by the deploy manifest: field — see
CAPABILITY.md):
| target | manifest | runtime |
|---|---|---|
| x86_64 + docker | package_manifest.yaml |
docker (docker/Dockerfile) |
| arm64 Jetson + docker | package_manifest.jetson-docker.yaml |
docker (docker/Dockerfile.jetson, L4T) |
| arm64 Jetson + native | package_manifest.jetson-native.yaml |
host ROS2 (scripts/start_native.sh) |
Add a target by adding a package_manifest.<target>.yaml plus a case branch
in scripts/build.sh — the rest of the package is unchanged.
The generated ROS 2 overlay intentionally builds only Robonix's custom map
interface package. Standard interfaces such as sensor_msgs continue to come
from the target's ROS 2 Humble installation, preserving its support libraries
and CMake exports for consumers such as cv_bridge.
Maps, modes and session state
Three databases, kept apart
RTAB-Map never writes a saved map. Knowing which file is which explains every rule below.
| database | path | who writes it |
|---|---|---|
| saved map | {MAPPING_MAPS_DIR}/{map_id}/rtabmap.db |
save_map only, once — immutable afterwards |
| runtime database | {MAPPING_RUNTIME_DB_DIR}/… (default /tmp/robonix-mapping-runtime) |
RTAB-Map, continuously. A mapping session gets a fresh empty one; a load gets a copy of the saved map |
| legacy default | ~/.ros/rtabmap.db |
nothing, in a normal deployment — kept only as a last-resort fallback for save_map |
A saved map directory holds the artifacts alongside the database:
maps/lab_3f/rtabmap.db occupancy.pgm occupancy.yaml occupancy.png cloud.pcd meta.yaml
map_ops keeps one record of which database is live and hands it to
save_map. Every entry point — deployment config, gRPC, MCP, the web UI —
updates the same record, so a map saved after a load snapshots the database
RTAB-Map actually holds open.
Startup configuration
map_mode and map_id in the deployment config choose the startup state.
There are two useful combinations:
# Build a new map. This is the default: omit both keys and you get it.
mapping:
config: {}
# Come up localized on a saved map — the stable-frame form used for tasks.
mapping:
config:
map_mode: localization
map_id: lab_3f
map_modedefaults tomapping, which always opens a fresh, empty runtime database. Amap_idgiven alongside it is ignored: it names a saved artifact, not a live session, and mapping never reopens one. There is no "start up and keep extending map X" configuration.map_mode: localizationrequiresmap_id, and fails to start if that map is missing — deliberately, rather than silently mapping from the boot pose. It copies the saved database to a runtime path and localizes against the copy, so the map frame is stable across restarts and Scene can load semantic state for the same id.reset_map: trueis only meaningful in mapping mode.
Runtime operations
| operation | changes the database | changes the mode | changes the frame |
|---|---|---|---|
save_map(map_id) |
no — snapshots the live database into a new saved map | no | no |
load_map(map_id) |
yes — copies the saved map and switches onto the copy | yes, to localization | yes, to the loaded map's frame |
switch_mode(mode) |
no | yes | no |
reset_map |
no — clears working memory, the file stays | back to mapping | yes — origin becomes the robot's current pose |
pose_estimate(x, y, θ) |
no | no | no |
delete_map(map_id) |
removes a saved map from disk | no | no |
Notes that matter in the field:
save_mappublishes once. Saving under an existingmap_idis refused; a corrected map goes under a new id.load_mapalways localizes. Amappingmode argument is accepted and coerced, because RTAB-Map only restores the saved occupancy grid when the database is opened for localization.reset_mapinvalidates coordinates. The rebuilt map does not share the old frame, so positions recorded against the previous map are stale. The lifecycle broadcast bumps its generation to say so.- Loading replaces the live session. Anything mapped since the last save is gone; save first.
Switching mode at runtime
The config's map_mode is only the startup default. switch_mode flips the
running RTAB-Map without touching the database or the frame.
Prefer a restart over a runtime switch. Going from localization back to
mapping is the risky direction, and the loaded map usually leaves the live view
when you do it. The web UI shows a standing warning while localized and asks
for confirmation before that switch. To build a new map, restart the service
with map_mode: mapping instead.
Why the loaded map disappears
Nothing is deleted — the map becomes a graph component the published map is not assembled from. Four steps, all in RTAB-Map 0.23.x:
- Entering localization calls
Memory::incrementMapId(), which opens a new session id and flushes short-term memory. Every load does this, because a load always enters localization. - While localized, each new node is dropped again rather than kept
(
moveToTrash(_lastSignature, …)), so the session id stays put. - Switching back to mapping only flips
Mem/IncrementalMemoryto true.Memory::addSignatureToStmlinks a new node to the previous one only when their session ids match, so the first node built after the switch gets no odometry link back into the loaded map. The graph now has two disconnected components. - The published map comes from
Rtabmap::optimizeCurrentMap, which optimizes the connected component around the current node. The loaded map is in the other component, so it is not in/map.
It comes back when RTAB-Map detects a loop closure between the two sessions: that link joins the components and the whole map returns. So the switch is only safe where relocalization can actually succeed. The database on disk is never affected either way.
Workflows
- Build the first map — start with no
map_id/map_mode, drive the space,save_map("lab_3f"). - Build another map — restart the service, then drive and save under a new id. Do not load an existing map first.
- Run tasks on a saved map — start with
map_mode: localizationandmap_id, orload_map(id)on a running service. - Correct a saved map — build a fresh session and save under a new id; a published map is immutable.
RTAB-Map UI
The RTAB-Map viewer starts with every mapping session so the graph, loop
closures and per-node grids are visible while the robot drives. It needs an X
server: scripts/start.sh forwards the host DISPLAY into the container, and
a session without one logs a line and continues headless. Set
MAPPING_ENABLE_VIZ=false to keep it off on a robot that has a display but no
operator.
Web UI (live map + runtime map ops)
A dependency-light operator page (stdlib http.server + Pillow) is enabled on
port 8091 by default; set deployment config webui_port: 0 to disable it.
It binds 127.0.0.1 by default because the map controls are unauthenticated.
An authenticated overlay deployment may explicitly set webui_host (or
MAPPING_WEBUI_HOST); otherwise use the local browser or an SSH tunnel.
It runs inside the mapping bridge process, so its buttons call the same
map_ops impls the gRPC/MCP capabilities use — no extra round trip — and it
reads the live /map + pose straight off the bridge's rclpy node.
- Live map canvas — occupancy grid + robot pose, with drag-to-pan, wheel-zoom, a 1 m grid, and double-click-to-fit. Same world-centered view model as scene's web UI (canvas backing-store pinned to display size, so click coordinates are exact).
- Save — snapshot the live map under a
map_id(writesrtabmap.db+occupancy.png/pgm/yaml+meta.yaml). - Library — every saved map with a thumbnail; Load re-localizes onto it, Del removes it from disk.
- Mode — flip Mapping ⇄ Localization at runtime; a badge + button highlight shows the mode the service reports, so a mode changed by config, MCP, a load or a reset shows up here too. Localization ⇒ mapping raises a warning first (see Switching mode at runtime).
- Reset map — wipe the live SLAM session and rebuild from scratch (for when mapping diverges). Note: the origin resets to the robot's current pose, so the rebuilt frame won't match the old map (origin drift).
- Set pose estimate — arm the button, then press where the robot is and drag the way it faces. The heading matters as much as the position: seeding the right spot facing backwards fails to relocalize just as a wrong spot does. The activity log records the seeded pose and, a few seconds later, where it converged and how far that is from your estimate.
- Live lidar overlay — the current range returns are drawn on the map in
green (2-D scan) and blue (point cloud). This is the check that answers "is
localization right": if the returns do not sit on the walls of the map, the
pose is wrong. Topics come from whatever Atlas resolved for
robonix/primitive/lidar/lidarandrobonix/primitive/lidar/lidar3d, so the overlay follows the deployment's capability bindings. When no 2-D scan capability is bound the page looks for aLaserScanon the graph instead and says which one it picked — a robot whose scan is projected downstream from a 3-D cloud (and therefore never declared) still gets its overlay. Pin one withwebui_scan_topicin the deployment config, orMAPPING_WEBUI_SCAN_TOPIC. This overlay follows the deployment's capability bindings — a Webots TIAGo shows its 2-D scan, a Ranger with a mid360 shows its cloud, and a deployment with no lidar bound simply has no overlay. Cloud returns are limited to a band around the sensor plane (MAPPING_WEBUI_CLOUD_Z_BAND, default 0.35 m) so they can be compared against a 2-D grid, and both are subsampled toMAPPING_WEBUI_MAX_POINTS(default 1200).
These are the same operations exposed as runtime RPC + MCP capabilities
(so Pilot can drive them too): save_map, load_map, pose_estimate,
switch_mode (the webui adds reset + delete on top). All work on the
running rtabmap without a redeploy — load/switch_mode call rtabmap's
runtime services and fall back to a restart with the config's map_mode /
map_id when those services aren't reachable.
The web UI has no auth — it's a LAN debug tool. Don't expose the port to an untrusted network.
Layout
mapping_rbnx/
├── package_manifest.yaml x86+docker (default)
├── package_manifest.jetson-docker.yaml arm64 Jetson + docker
├── package_manifest.jetson-native.yaml arm64 Jetson + host ROS2
├── CAPABILITY.md capability surface + config spec
├── src/mapping_rbnx/atlas_bridge.py cap registration, sensor discovery, persistence
├── src/mapping_rbnx/webui.py operator page server + ROS subscriptions
├── src/mapping_rbnx/webui_static/ the page itself (index.html, app.js, style.css)
├── src/mapping_rbnx/map_to_odom_bridge.py optional split-odometry TF bridge
├── src/mapping_rbnx/odom_bridge_math.py planar transform and interpolation helpers
├── launch/rtabmap_2d.launch.py sensor-agnostic rtabmap launch
├── scripts/
│ ├── build.sh per-target build
│ ├── build_ros2_overlay.sh isolated map interface build
│ ├── start.sh native↔docker dispatch
│ ├── start_engine.sh in-container SLAM launcher
│ ├── start_native.sh host-process launcher
│ └── save_map.py offline map snapshot (pgm/png/pcd/meta)
└── docker/ Dockerfile, Dockerfile.jetson, compose
Troubleshooting
/mapnever populates — a provider binding is missing or points to the wrong provider. Check the[start_engine] rtabmap scan2d=… scan3d=…line.map_mode=localizationerrors "no saved map" — run amappingsession with thatmap_idfirst, and confirmMAPPING_MAPS_DIRis the same path (mounted) across runs.- Map origin drifts between runs — you're in
mappingmode (origin = boot pose). Uselocalizationto re-anchor to the saved map. save_mapsays "no live rtabmap database found to snapshot" — nothing has opened a database yet, or the recorded one was removed. The message lists the paths it tried. A service that has been running and mapping always has one; if this appears right after a load, the deployment predates the shared live-database record and should be updated.- The map "disappeared" after switching to mapping mode — expected, see Why the loaded map disappears. It returns on a loop closure with the loaded session; the saved map on disk is intact either way. Build new maps from a restart instead of a runtime switch.
License: MulanPSL-2.0