docs(perception): define traversability evaluation sequence
This commit is contained in:
DCCONSTRUCTIONS
@@ -189,6 +189,13 @@ sealed Current/Patchwork++ comparison rejected Patchwork++ for navigation:
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despite much lower latency and a small Ground-IoU gain, obstacle non-ground
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recall regressed from `80.46%` to `69.70%`.
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Operator review of the later M4.8R3 LOW-STEP replay rejected its connected-
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component camera boxes as the product representation for general static
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obstacles. The replacement evaluation is terrain-relative and sequential:
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GSeg3D plus Nav2 Ground Consistency first, TRAVEL as the class-free challenger,
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and nvblox only as a separately measured occupancy/ESDF candidate. See the
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[traversability and static-obstacle stack decision](docs/23_TRAVERSABILITY_AND_STATIC_OBSTACLE_STACK_DECISION.md).
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See [the Dataset Gateway plan](docs/14_LIDAR_DATASET_GATEWAY.md),
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[the laboratory run canon](docs/15_LABORATORY_RUN_CANON.md) and
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[ADR 0021](docs/adr/0021-dataset-gateway-representation-boundary.md).
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@@ -0,0 +1,67 @@
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{
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"schema_version": "missioncore.traversability-candidate-manifest/v1",
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"decision_document": "docs/23_TRAVERSABILITY_AND_STATIC_OBSTACLE_STACK_DECISION.md",
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"frozen_utc": "2026-08-26T13:53:55Z",
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"source_contract": {
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"source_id": "RAVNOVES00",
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"expected_timeline_frames": 4489,
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"input_representation": "registered-vendor-map-increment-plus-causal-local-support/v1",
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"future_frames_allowed": false,
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"missing_support_means_free": false
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},
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"candidates": [
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{
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"sequence": 1,
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"candidate_id": "gseg3d-ground-consistency",
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"role": "primary",
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"components": [
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{
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"repository": "https://github.com/dfki-ric/ground_segmentation_ros2.git",
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"revision": "5c5ba6f5ca0d682db2d59b2ad2f6a317ee938b95",
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"observed_ref": "refs/heads/master",
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"license": "BSD-3-Clause"
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},
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{
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"repository": "https://github.com/dfki-ric/nav2_ground_consistency_costmap_plugin.git",
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"revision": "41cec620efba6c370dccfc59a6ec1134775ff48a",
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"observed_ref": "refs/heads/main",
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"license": "BSD-3-Clause"
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}
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]
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},
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{
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"sequence": 2,
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"candidate_id": "travel",
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"role": "class-free-challenger",
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"components": [
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{
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"repository": "https://github.com/url-kaist/TRAVEL.git",
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"revision": "95dc2fbd66a343efd9060c45a5711b6307a950a4",
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"observed_ref": "refs/heads/main",
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"license": "GPL-3.0"
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}
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]
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},
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{
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"sequence": 3,
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"candidate_id": "isaac-ros-nvblox",
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"role": "separate-gpu-occupancy-esdf-probe",
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"components": [
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{
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"repository": "https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_nvblox.git",
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"revision": "ef47346399c71a4342c03bdbec2136ec735da4b8",
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"observed_ref": "refs/tags/v4.6-0",
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"license": "Apache-2.0"
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}
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]
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}
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],
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"execution_policy": {
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"heavy_candidates_run_sequentially": true,
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"allow_parallel_gauss_compute": false,
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"allow_source_mutation": false,
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"allow_navigation_or_actuation": false,
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"allow_camera_resize_or_rectification": false,
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"allow_new_semantic_model": false
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}
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}
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@@ -1539,6 +1539,11 @@ production navigation cutover. The result remains replay-simulated;
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physical-live authority, commands, actuation, planner-authoritative free space
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and collision-safety acceptance are false. The next milestone boundary is
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M4.9 recorded-realtime release-candidate validation using this frozen graph.
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Subsequent operator visual review rejected the LOW-STEP connected-component
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camera boxes as a general static-obstacle product path. That decision does not
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alter the immutable M4.8R3 runtime evidence; it redirects the next perception
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evaluation to the terrain-relative sequence in
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[`docs/23_TRAVERSABILITY_AND_STATIC_OBSTACLE_STACK_DECISION.md`](23_TRAVERSABILITY_AND_STATIC_OBSTACLE_STACK_DECISION.md).
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## Implementation order
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@@ -0,0 +1,278 @@
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# Traversability and class-free static-obstacle stack decision
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Date: 2026-08-26
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Status: accepted for sequential recorded-replay evaluation; not accepted for
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navigation or actuation
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## Decision summary
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Mission Core stops treating the M4.8R3 `LOW-STEP` connected-component and
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camera-box projection as the product path for general static-obstacle
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perception. M4.8R3 remains immutable evidence that a bounded occupied-only
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heuristic can execute in the realtime envelope. Operator review of the complete
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visual result rejected its obstacle quality and representation:
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- isolated vegetation, curb edges and sparse returns become false obstacles;
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- bins, carts, thin posts, railings and hemispheres are inconsistently lost;
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- spatially unrelated points merge into large rectangular camera regions;
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- one-frame components flicker without ground/obstacle evidence competition;
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- 2D rectangles erase the free passage between separate 3D obstacles.
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This is an abstraction failure, not a threshold-tuning failure. A navigation
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system requires a terrain-relative occupancy and traversability product, not a
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detector that attempts to name every static object and not a bounding box as
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the safety primitive.
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The sequential evaluation order is:
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1. **GSeg3D + Nav2 Ground Consistency + Nav2 Costmap** — primary candidate.
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2. **TRAVEL + the same costmap boundary** — class-free challenger if the
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primary candidate misses compact or thin obstacles or merges passages.
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3. **Isaac ROS nvblox** — separate GPU occupancy/ESDF candidate after the CPU
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terrain contour is measured; it is not stacked into the first test.
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RF-DETR remains the semantic risk provider for people, children, animals,
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cars, trucks, motorcycles and bicycles. It does not decide the presence or
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shape of an unknown static obstacle. Native `800x600` fisheye input remains
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unchanged.
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## Required product representation
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```text
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LiDAR + pose + optional IMU
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v
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terrain-relative ground / non-ground evidence
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v
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temporally stable local occupancy and UNKNOWN support state
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v
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robot-footprint collision cost + traversability
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+----> planner / collision monitor (future authority gate)
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+----> camera projection (diagnostic visualization only)
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camera RF-DETR ----> dynamic semantic risk hints ----------------+
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```
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The canonical safety output is a costmap/elevation/occupancy product. Camera
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boxes may be derived for operator review, but a box must never be the source of
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occupied cells, clearance, passage width or a control action.
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## Candidate A — GSeg3D and Ground Consistency
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### GSeg3D
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[DFKI GSeg3D ROS 2](https://github.com/dfki-ric/ground_segmentation_ros2)
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is a BSD-3-Clause ROS 2 component for CPU realtime processing of 3D LiDAR. It
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publishes separate ground and obstacle point clouds and provides:
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- optional IMU gravity alignment;
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- two-phase coarse/fine ground segmentation;
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- configurable slope, local height and inlier thresholds;
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- ROS 2 Humble and Jazzy support;
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- no task-specific dataset or neural-network inference.
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Mission Core evaluates it as the first replacement for the current local
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height connected-component heuristic.
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### Nav2 Ground Consistency
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[DFKI Ground Consistency](https://github.com/dfki-ric/nav2_ground_consistency_costmap_plugin)
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is a BSD-3-Clause Nav2 costmap layer and is included in the current
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[Nav2 outdoor 3D-LiDAR tutorial](https://ros-navigation.github.io/mkdocs.nav2.org/rolling/tutorials/general_tutorials/navigation2_with_ground_consistency_layer/navigation2_with_ground_consistency_layer/).
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It consumes ground and non-ground point clouds and supplies the missing product
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semantics:
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- ground and obstacle evidence compete per costmap cell;
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- evidence accumulates and decays instead of trusting one point in one frame;
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- obstacle height is evaluated relative to local ground;
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- robot height and minimum clearance are explicit configuration inputs;
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- sparse cells can use bounded neighboring-ground interpolation;
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- a cell without reliable support can fail closed instead of becoming free.
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The first test keeps all free-space and actuation authority false. The layer is
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evaluated only as a recorded-replay occupancy provider.
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### Nav2 boundary
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[Nav2 Costmap 2D](https://docs.nav2.org/configuration/packages/configuring-costmaps.html)
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provides footprint-aware obstacle, voxel and inflation layers. A later physical
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gate may add the independent
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[Nav2 Collision Monitor](https://docs.nav2.org/rolling/configuration_and_development/configuration_guide/core_servers/collision_monitor/configuring_collision_monitor_node/),
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but recorded replay does not publish commands.
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## Candidate B — TRAVEL
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[TRAVEL](https://github.com/url-kaist/TRAVEL) performs class-free traversable
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ground detection and above-ground instance clustering. Its ROS 2 wrapper is
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verified by the project on Humble and Jazzy. The published evaluation reports
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roughly `20-30 Hz` and explicitly targets safe navigation in unseen urban and
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wild environments without assigning names such as pole, vehicle or wall.
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TRAVEL is valuable when individual compact obstacles and the gaps between them
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must remain spatially distinct. Its GPL-3.0 license prevents silent admission
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into a proprietary product runtime. It is initially a benchmark/challenger;
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distribution consequences require a separate decision.
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Primary reference:
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[TRAVEL paper](https://arxiv.org/abs/2206.03190).
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## Candidate C — Isaac ROS nvblox
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[Isaac ROS nvblox](https://nvidia-isaac-ros.github.io/repositories_and_packages/isaac_ros_nvblox/index.html)
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uses GPU-accelerated TSDF/ESDF reconstruction from depth and/or 3D LiDAR and
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publishes a Nav2 costmap. Current NVIDIA documentation supports ROS 2 Jazzy on
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x86_64 with an Ampere-or-newer NVIDIA GPU and at least 8 GiB VRAM; Worker 006's
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RTX 4090 is inside that hardware class.
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Nvblox is evaluated separately because it answers dense occupied-space and
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clearance questions well, but it is not by itself a complete terrain-relative
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traversability classifier. Its official kernel timings are not an end-to-end
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Mission Core FPS guarantee.
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## Candidates not admitted to the first sequence
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| Candidate | Reason not first |
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| --- | --- |
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| Autoware Universe | Mature road-vehicle perception and occupancy, but a large automotive/lane-driving stack for this rover-sized contour. |
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| Offroad-Nav 2026 | Relevant complete pipeline, but currently ROS 1 Noetic; ROS 2 port is in development and the real-robot branch is not published. |
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| `elevation_mapping_cupy` | Strong GPU elevation-map implementation, but the maintained integration remains ROS 1/catkin. It is retained as an algorithmic reference. |
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| CMU AEDE/FAR/TARE | Proven research navigation components, but not the shortest supported ROS 2 product baseline for this test. |
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| Additional image segmentation model | Consumes GPU and still cannot establish metric support, clearance or unknown space. |
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## Source representation boundary
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`RAVNOVES00` does not contain a conventional complete raw LiDAR scan per video
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frame. Its `lio_pcl` stream is a registered vendor-map increment in the SLAM
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map frame. Missing republication is not free-space evidence.
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Therefore every candidate run must preserve three distinct products:
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1. exact current registered increment;
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2. bounded causal rolling support/occupancy in the map frame;
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3. candidate ground/non-ground/costmap output with source lineage.
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For Candidate A, the evaluation adapter may present a bounded causal local
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cloud in the current body frame. It may not use future frames, clear cells from
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missing points, or relabel unobserved space as free. Dynamic-object semantics
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remain outside this static replay adapter.
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## Operator-reviewed regression set
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The following RAVNOVES00 source frames are mandatory review anchors. They are
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operator-reviewed engineering cases, not independent statistical ground truth.
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| Frame | Required observation |
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| ---: | --- |
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| 171 | The grass/curb region must not become a large blocking object; the visible bin must remain obstacle evidence when supported by LiDAR. |
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| 306 | The cart and right hemisphere must not be lost while curb corners become dominant. |
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| 368 | The hemisphere extent must stay compact; the right railing must remain obstacle evidence. |
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| 402 | The near hemisphere must not inflate into a camera-sized rectangular exclusion zone. |
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| 450 | Curb/ramp terrain must be evaluated relative to local ground instead of becoming arbitrary boxes. |
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| 509 | Isolated vegetation or sparse returns must not immediately become a stable blocking object. |
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| 525 | Sparse local returns must not merge into one large occupied camera rectangle. |
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| 744 | The grass/curb strip must not be promoted into a wall. |
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| 1122 | The compact hemisphere and both thin posts must be represented when LiDAR support is present. |
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| 1856 | Two posts remain separate, two hemispheres remain separate, and the passages between them remain explicit. |
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## Acceptance contract
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### Quality
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- Static obstacle output is class-free and geometry-backed.
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- All supported critical anchors above are occupied or conservatively unknown,
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never false-free.
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- Vegetation, curb edges and isolated returns do not create large persistent
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lethal regions without sustained non-ground evidence.
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- Separate posts and hemispheres remain separate at the costmap resolution.
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- A camera rectangle cannot merge two distinct occupied regions or erase their
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gap.
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- Unobserved support, drop-offs and no-return regions remain `UNKNOWN/LETHAL`
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until positive support is observed.
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- No manual object-class annotation or detector training is permitted for this
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gate.
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### Realtime and resource envelope
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- Process all `4,489` timeline frames with zero unaccounted loss.
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- Isolated candidate output keeps up with at least the recorded `10 Hz` source
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cadence.
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- Integrated graph FPS regression is at most `5%` relative to the immutable
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M4.8R3 `11.79902 FPS` reference.
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- Candidate-stage p95 latency is at most `25 ms` and p99 at most `50 ms` in the
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recorded replay contour.
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- The primary CPU candidate does not add another neural model or consume the
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RF-DETR GPU budget.
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- CPU, RAM, GPU, VRAM, queue depth, supersession and output age are recorded;
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no result is accepted only because it looks good in selected frames.
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### Authority
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Passing this document's tests accepts a recorded-replay perception provider.
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It does not accept physical free space, navigation, commands, actuation,
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collision safety or a robot body model.
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## Sequential execution plan
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### T0 — Worker and source preflight
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- Inventory Worker 006 OS/WSL, ROS 2, Docker, compiler, CPU/RAM and RTX 4090.
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- Confirm the immutable RAVNOVES00 source and accepted M4.8R3 result locally on
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the worker without copying private source evidence back to the Mac.
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- Record a content-addressed candidate manifest and exact upstream revisions.
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The first T0 snapshot is recorded in
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[`experiments/perception/M49_T0_TRAVERSABILITY_PREFLIGHT_2026-08-26.md`](../experiments/perception/M49_T0_TRAVERSABILITY_PREFLIGHT_2026-08-26.md).
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Exact upstream revisions are frozen in
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[`config/perception/m49-traversability-candidate-manifest-v1.json`](../config/perception/m49-traversability-candidate-manifest-v1.json).
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T0 found the source and the accepted raw M4.8R3 run intact, but did not start a
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build: the parallel GAUSS contour was active and free Worker memory had fallen
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to approximately `669 MiB`. That is a resource-admission stop, not a candidate
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failure.
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### T1 — Candidate A isolated qualification
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- Build GSeg3D and Ground Consistency in a new isolated `ndc-` worker contour.
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- Run upstream sample/demo data first to prove the unmodified components.
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- Measure component latency and memory before adding Mission Core adapters.
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### T2 — Candidate A RAVNOVES00 replay
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- Feed the bounded causal local cloud with exact pose lineage.
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- Produce ground, non-ground, occupancy and unknown layers for all frames.
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- Review the ten mandatory anchors and compute full-run stability/resource
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metrics.
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- Do not draw system camera boxes until the costmap result is sealed.
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### T3 — Candidate B challenger
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- Run TRAVEL against the identical source representation and anchors.
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- Compare compact-obstacle recall, passage preservation, temporal stability and
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CPU cost against Candidate A.
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- Stop if Candidate A already passes and TRAVEL adds no measurable value that
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justifies GPL runtime implications.
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### T4 — Candidate C occupancy/ESDF probe
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- Run nvblox separately with RF-DETR disabled for the isolated probe.
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- Measure GPU/VRAM and 3D occupied-space quality.
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- Admit it only if it supplies a measured capability missing from the accepted
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CPU terrain contour inside the one-RTX-4090 production ceiling.
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### T5 — Product integration gate
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- Select one terrain provider and at most one justified occupancy complement.
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- Re-enable the frozen RF-DETR semantic-risk provider.
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- Repeat complete recorded-source-paced load acceptance.
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- Publish a LAB only after the costmap/elevation outputs and limitations are
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sealed.
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## Immediate next action
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||||
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Resume T1 for Candidate A only after the Worker resource gate in the T0 report
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passes. No LOW-STEP tuning, new object model, camera resize, fisheye
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||||
rectification, manual dataset or parallel heavy Worker job is authorized by
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this decision.
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@@ -0,0 +1,95 @@
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# M4.9 T0 traversability candidate preflight — 2026-08-26
|
||||
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||||
Status: source and revision preflight complete; Candidate A build not started
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||||
because the Worker resource-admission gate was closed
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## Purpose
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||||
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||||
T0 verifies that the first terrain-relative candidate can be evaluated against
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||||
the immutable Mission Core source without colliding with another heavy Worker
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||||
job. It does not qualify obstacle quality, realtime performance, navigation or
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||||
actuation.
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||||
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||||
The governing decision is
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||||
[`docs/23_TRAVERSABILITY_AND_STATIC_OBSTACLE_STACK_DECISION.md`](../../docs/23_TRAVERSABILITY_AND_STATIC_OBSTACLE_STACK_DECISION.md).
|
||||
The exact upstream revisions are frozen in
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||||
[`config/perception/m49-traversability-candidate-manifest-v1.json`](../../config/perception/m49-traversability-candidate-manifest-v1.json).
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||||
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||||
## Read-only Worker snapshot
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||||
|
||||
Observed at `2026-08-26T13:53:55Z` on Worker 006
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||||
(`DESKTOP-OPJ8J04`):
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||||
|
||||
| Item | Observation |
|
||||
| --- | --- |
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||||
| OS | Windows 11 Pro, version `10.0.26200`, build `26200` |
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||||
| CPU | Intel Core i9-13900KF, 24 cores / 32 logical processors |
|
||||
| Physical memory | `100,502,708 KiB` visible; `685,344 KiB` free at the final snapshot |
|
||||
| GPU | NVIDIA GeForce RTX 4090, driver `610.47`, `24,564 MiB` total VRAM |
|
||||
| GPU snapshot | `9,131 MiB` used, `47%` utilization, `44 C` |
|
||||
| WSL | `docker-desktop` running; Ubuntu 24.04, MissionCore-Sim and MissionCore-CVAT stopped |
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||||
| Mission Core inference | Canonical `ndc-mission-core-triton` remained healthy |
|
||||
| Parallel work | GAUSS gateway and builder containers were healthy and active |
|
||||
|
||||
No container, WSL distribution, service or source file was started, stopped,
|
||||
rebuilt or modified during this inspection.
|
||||
|
||||
## Source and baseline evidence
|
||||
|
||||
The canonical RAVNOVES00 camera index, LiDAR pack, local-surface pack and native
|
||||
fisheye video are present on the Worker at their existing content-addressed
|
||||
paths. The accepted raw M4.8R3 full run is present at:
|
||||
|
||||
`D:\NDC_MISSIONCORE\runtime\results\m48r3-static-occupancy-shadow\ravnoves00-full-exact6-near8-12fps-v1`
|
||||
|
||||
Its `result.json` SHA-256 is
|
||||
`0fe50546801d1284eb7af7ffcee0fbfc98985094c678256007b10eade0e54488`.
|
||||
The raw result reports:
|
||||
|
||||
- source `RAVNOVES00`, `4,489` frames at requested `12 Hz`;
|
||||
- integrated runtime gate passed;
|
||||
- graph completion p95 `56.74324 ms`;
|
||||
- geometry p95/p99 `8.420913/13.732692 ms`;
|
||||
- GPU utilization p95/maximum `54%/58%`;
|
||||
- maximum GPU memory `9,743 MiB`.
|
||||
|
||||
The separately sealed Mission Core product identity remains
|
||||
`m48r3-static-occupancy-shadow-d1577870b098bcd0b67cc51798234f224b348ad3954ead72f3ce6df414875a29`.
|
||||
This T0 check does not reopen or alter that evidence.
|
||||
|
||||
## Frozen candidates
|
||||
|
||||
| Order | Candidate | Exact revision | Admission role |
|
||||
| ---: | --- | --- | --- |
|
||||
| 1 | DFKI GSeg3D | `5c5ba6f5ca0d682db2d59b2ad2f6a317ee938b95` | Primary terrain-relative ground/non-ground provider |
|
||||
| 1 | DFKI Nav2 Ground Consistency | `41cec620efba6c370dccfc59a6ec1134775ff48a` | Primary temporal costmap evidence layer |
|
||||
| 2 | TRAVEL | `95dc2fbd66a343efd9060c45a5711b6307a950a4` | Class-free challenger |
|
||||
| 3 | Isaac ROS nvblox `v4.6-0` | `ef47346399c71a4342c03bdbec2136ec735da4b8` | Separate GPU occupancy/ESDF probe |
|
||||
|
||||
These SHAs were resolved directly from the official upstream repositories. A
|
||||
moving branch name is not an executable test identity.
|
||||
|
||||
## Resource-admission result
|
||||
|
||||
**T1 was intentionally not started.** Free physical memory fell from roughly
|
||||
`3.3 GiB` during the first inventory to `669 MiB` at the final snapshot while
|
||||
the parallel GAUSS contour was active. Starting a ROS 2 image build or another
|
||||
replay in that state would make the measurement invalid and could destabilize
|
||||
unrelated work.
|
||||
|
||||
Candidate A may start only when all of the following are true:
|
||||
|
||||
1. no unrelated heavy Worker build or replay is active;
|
||||
2. free physical memory is at least `16 GiB` before the build;
|
||||
3. GPU utilization is at most `10%` before an integrated replay, unless the
|
||||
active GPU process is an explicitly admitted part of that replay;
|
||||
4. canonical Mission Core Triton is healthy and is not stopped or replaced;
|
||||
5. the candidate uses a new `ndc-` isolated build/runtime contour.
|
||||
|
||||
## Next command boundary
|
||||
|
||||
The next authorized action is T1 Candidate A upstream qualification: build the
|
||||
pinned GSeg3D and Ground Consistency revisions in an isolated ROS 2 contour,
|
||||
run their upstream sample path, and record build identity, latency and memory.
|
||||
RAVNOVES00 replay begins only after that unmodified upstream qualification
|
||||
passes.
|
||||
Reference in New Issue
Block a user