feat: add RELLIS dataset compatibility smoke

apps/control-station/src/core/lidar/datasetGateway.ts

@@ -3,6 +3,57 @@ export type DatasetRepresentationId =
   | "normalized-scan"
   | "rolling-local-map";
 
+export type DatasetSourceAdmissionStatus =
+  | "blocked-storage-policy"
+  | "ready-for-download"
+  | "ready-for-smoke"
+  | "downloading"
+  | "downloaded"
+  | "verifying"
+  | "verified"
+  | "frame-ready"
+  | "smoke-ready";
+
+export interface DatasetSource {
+  sourceId: string;
+  sourceKind: "goose" | "rellis";
+  displayName: string;
+  role: string;
+  license: string;
+  commercialUse:
+    | "allowed-with-share-alike"
+    | "research-only-license-review-required";
+  format: string;
+  frameSemantics: "one-lidar-revolution";
+  sensor: string;
+  platforms: string[];
+  superclasses: string[];
+  smokeExampleMb: number | null;
+  primaryScanArchiveGb: number;
+  labelArchiveGb: number | null;
+  posesArchiveGb: number | null;
+  fragmentCount: number;
+  annotatedScanCount: number;
+  admissionStatus: DatasetSourceAdmissionStatus;
+  archive: {
+    bytesTransferred: number;
+    totalBytes: number;
+    sizeBytes: number | null;
+    sha256: string | null;
+    integrity: string;
+    vendorChecksumAvailable: false;
+  } | null;
+  frame: {
+    frameId: string;
+    pointCount: number;
+    semanticClassCount: number;
+    groundTruthGroundFraction: number;
+    previewPointCount: number;
+    previewSha256: string | null;
+    previewAvailable: true;
+  } | null;
+}
+
 export interface DatasetGatewayCatalog {
   storage: {
     configured: boolean;
@@ -13,42 +64,7 @@ export interface DatasetGatewayCatalog {
     requiredWindowsRoot: string;
     requiredWslRoot: string;
   };
-  source: {
-    sourceId: string;
-    displayName: string;
-    role: string;
-    license: string;
-    format: string;
-    frameSemantics: "one-lidar-revolution";
-    platforms: string[];
-    superclasses: string[];
-    validationArchiveGb: number;
-    admissionStatus:
-      | "blocked-storage-policy"
-      | "ready-for-download"
-      | "downloading"
-      | "downloaded"
-      | "verifying"
-      | "verified"
-      | "frame-ready";
-    archive: {
-      bytesTransferred: number;
-      totalBytes: number;
-      sizeBytes: number | null;
-      sha256: string | null;
-      integrity: string;
-      vendorChecksumAvailable: false;
-    } | null;
-    frame: {
-      frameId: string;
-      pointCount: number;
-      semanticClassCount: number;
-      groundTruthGroundFraction: number;
-      previewPointCount: number;
-      previewSha256: string;
-      previewAvailable: true;
-    } | null;
-  };
+  sources: DatasetSource[];
   representations: Array<{
     id: DatasetRepresentationId;
     title: string;
@@ -72,7 +88,7 @@ export interface DatasetGatewayCatalog {
 }
 
 export interface DatasetNativeScanPreview {
-  sourceId: "goose-3d/v2025-08-22";
+  sourceId: "goose-3d/v2025-08-22" | "rellis-3d/v1.1";
   frameId: string;
   sourcePointCount: number;
   pointCount: number;
@@ -81,13 +97,23 @@ export interface DatasetNativeScanPreview {
   semanticLabelIds: number[];
   semanticRgb0To255: number[];
   groundTruthGround: number[];
+  evaluationMask: number[];
   classes: Array<{
     labelId: number;
     className: string;
     hex: string;
-    challengeCategoryId: number;
-    challengeCategoryName: string;
+    challengeCategoryId: number | null;
+    challengeCategoryName: string | null;
+    groundTarget: "ground" | "non-ground" | "ignore" | null;
+    sourcePointCount: number | null;
   }>;
+  coordinateFrame: {
+    frameId: string;
+    x: "forward";
+    y: "left";
+    z: "up";
+  } | null;
+  compatibilitySmokeOnly: boolean;
 }
 
 export interface DatasetGroundMetrics {
@@ -225,7 +251,7 @@ export function parseDatasetGatewayCatalog(
 ): DatasetGatewayCatalog {
   const source = record(value, "Dataset Gateway");
   if (
-    source.schema_version !== "missioncore.dataset-gateway-catalog/v2"
+    source.schema_version !== "missioncore.dataset-gateway-catalog/v3"
     || source.access !== "read-only"
   ) {
     throw new DatasetGatewayContractError("Dataset Gateway contract несовместим");
@@ -247,85 +273,158 @@ export function parseDatasetGatewayCatalog(
     throw new DatasetGatewayContractError("storage.attestation: неизвестное значение");
   }
   const sources = array(source.sources, "sources");
-  if (sources.length !== 1) {
-    throw new DatasetGatewayContractError("Ожидался один первичный dataset source");
+  if (sources.length !== 2) {
+    throw new DatasetGatewayContractError("Ожидались два закреплённых dataset source");
   }
-  const dataset = record(sources[0], "sources[0]");
-  const download = record(dataset.download, "source.download");
-  const admission = record(dataset.admission, "source.admission");
-  if (download.automatic !== false) {
-    throw new DatasetGatewayContractError("Большой dataset нельзя загружать автоматически");
-  }
-  const admissionStatus = admission.status;
+  const parsedSources = sources.map((value, index): DatasetSource => {
+    const dataset = record(value, `sources[${index}]`);
+    const sourceKind = string(dataset.source_kind, "source_kind", true);
+    const sourceId = string(dataset.source_id, "source_id", true);
+    if (
+      (sourceKind !== "goose" || sourceId !== "goose-3d/v2025-08-22")
+      && (sourceKind !== "rellis" || sourceId !== "rellis-3d/v1.1")
+    ) {
+      throw new DatasetGatewayContractError("Dataset source identity неизвестна");
+    }
+    if (dataset.frame_semantics !== "one-lidar-revolution") {
+      throw new DatasetGatewayContractError("Dataset frame semantics несовместима");
+    }
+    const download = record(dataset.download, `sources[${index}].download`);
+    const statistics = record(dataset.statistics, `sources[${index}].statistics`);
+    const admission = record(dataset.admission, `sources[${index}].admission`);
+    if (download.automatic !== false) {
+      throw new DatasetGatewayContractError(
+        "Большой dataset нельзя загружать автоматически",
+      );
+    }
+    const admissionStatus = admission.status;
+    if (
+      admissionStatus !== "ready-for-download"
+      && admissionStatus !== "ready-for-smoke"
+      && admissionStatus !== "blocked-storage-policy"
+      && admissionStatus !== "downloading"
+      && admissionStatus !== "downloaded"
+      && admissionStatus !== "verifying"
+      && admissionStatus !== "verified"
+      && admissionStatus !== "frame-ready"
+      && admissionStatus !== "smoke-ready"
+    ) {
+      throw new DatasetGatewayContractError("source admission status неизвестен");
+    }
+    const archive = admission.archive === null
+      ? null
+      : record(admission.archive, `sources[${index}].admission.archive`);
+    const archiveValue = archive
+      ? {
+          bytesTransferred: number(
+            archive.bytes_transferred,
+            "archive.bytes_transferred",
+          ),
+          totalBytes: number(archive.total_bytes, "archive.total_bytes"),
+          sizeBytes: nullableNumber(archive.size_bytes, "archive.size_bytes"),
+          sha256: nullableDigest(archive.sha256, "archive.sha256"),
+          integrity: string(archive.integrity, "archive.integrity", true),
+          vendorChecksumAvailable: (() => {
+            if (archive.vendor_checksum_available !== false) {
+              throw new DatasetGatewayContractError(
+                "archive.vendor_checksum_available: ожидался false",
+              );
+            }
+            return false as const;
+          })(),
+        }
+      : null;
+    const admittedFrame = admission.frame === null
+      ? null
+      : record(admission.frame, `sources[${index}].admission.frame`);
+    const frameValue = admittedFrame
+      ? {
+          frameId: string(admittedFrame.frame_id, "frame.frame_id", true),
+          pointCount: number(admittedFrame.point_count, "frame.point_count"),
+          semanticClassCount: number(
+            admittedFrame.semantic_class_count,
+            "frame.semantic_class_count",
+          ),
+          groundTruthGroundFraction: number(
+            admittedFrame.ground_truth_ground_fraction,
+            "frame.ground_truth_ground_fraction",
+          ),
+          previewPointCount: number(
+            admittedFrame.preview_point_count,
+            "frame.preview_point_count",
+          ),
+          previewSha256: nullableDigest(
+            admittedFrame.preview_sha256,
+            "frame.preview_sha256",
+          ),
+          previewAvailable: (() => {
+            if (admittedFrame.preview_available !== true) {
+              throw new DatasetGatewayContractError(
+                "frame.preview_available: ожидался true",
+              );
+            }
+            return true as const;
+          })(),
+        }
+      : null;
+    if (
+      sourceKind === "goose"
+      && frameValue
+      && frameValue.previewSha256 === null
+    ) {
+      throw new DatasetGatewayContractError("GOOSE frame.preview_sha256 отсутствует");
+    }
+    const commercialUse = dataset.commercial_use;
+    if (
+      commercialUse !== "allowed-with-share-alike"
+      && commercialUse !== "research-only-license-review-required"
+    ) {
+      throw new DatasetGatewayContractError("Dataset license scope неизвестен");
+    }
+    return {
+      sourceId,
+      sourceKind,
+      displayName: string(dataset.display_name, "display_name"),
+      role: string(dataset.role, "role", true),
+      license: string(dataset.license, "license"),
+      commercialUse,
+      format: string(dataset.format, "format", true),
+      frameSemantics: "one-lidar-revolution",
+      sensor: string(dataset.sensor, "sensor"),
+      platforms: displayStrings(dataset.platforms, "platforms"),
+      superclasses: strings(dataset.superclasses, "superclasses"),
+      smokeExampleMb: nullableNumber(
+        download.smoke_example_mb,
+        "smoke_example_mb",
+      ),
+      primaryScanArchiveGb: number(
+        download.primary_scan_archive_gb,
+        "primary_scan_archive_gb",
+      ),
+      labelArchiveGb: nullableNumber(
+        download.label_archive_gb,
+        "label_archive_gb",
+      ),
+      posesArchiveGb: nullableNumber(
+        download.poses_archive_gb,
+        "poses_archive_gb",
+      ),
+      fragmentCount: number(statistics.fragment_count, "fragment_count"),
+      annotatedScanCount: number(
+        statistics.annotated_scan_count,
+        "annotated_scan_count",
+      ),
+      admissionStatus,
+      archive: archiveValue,
+      frame: frameValue,
+    };
+  });
   if (
-    admissionStatus !== "ready-for-download"
-    && admissionStatus !== "blocked-storage-policy"
-    && admissionStatus !== "downloading"
-    && admissionStatus !== "downloaded"
-    && admissionStatus !== "verifying"
-    && admissionStatus !== "verified"
-    && admissionStatus !== "frame-ready"
+    parsedSources[0]?.sourceKind !== "goose"
+    || parsedSources[1]?.sourceKind !== "rellis"
   ) {
-    throw new DatasetGatewayContractError("source admission status неизвестен");
+    throw new DatasetGatewayContractError("Dataset source order несовместим");
   }
-  const archive = admission.archive === null
-    ? null
-    : record(admission.archive, "source.admission.archive");
-  const archiveValue = archive
-    ? {
-        bytesTransferred: number(
-          archive.bytes_transferred,
-          "archive.bytes_transferred",
-        ),
-        totalBytes: number(archive.total_bytes, "archive.total_bytes"),
-        sizeBytes: nullableNumber(archive.size_bytes, "archive.size_bytes"),
-        sha256: nullableDigest(archive.sha256, "archive.sha256"),
-        integrity: string(archive.integrity, "archive.integrity", true),
-        vendorChecksumAvailable: (() => {
-          if (archive.vendor_checksum_available !== false) {
-            throw new DatasetGatewayContractError(
-              "archive.vendor_checksum_available: ожидался false",
-            );
-          }
-          return false as const;
-        })(),
-      }
-    : null;
-  const admittedFrame = admission.frame === null
-    ? null
-    : record(admission.frame, "source.admission.frame");
-  const frameValue = admittedFrame
-    ? {
-        frameId: string(admittedFrame.frame_id, "frame.frame_id", true),
-        pointCount: number(admittedFrame.point_count, "frame.point_count"),
-        semanticClassCount: number(
-          admittedFrame.semantic_class_count,
-          "frame.semantic_class_count",
-        ),
-        groundTruthGroundFraction: number(
-          admittedFrame.ground_truth_ground_fraction,
-          "frame.ground_truth_ground_fraction",
-        ),
-        previewPointCount: number(
-          admittedFrame.preview_point_count,
-          "frame.preview_point_count",
-        ),
-        previewSha256: nullableDigest(
-          admittedFrame.preview_sha256,
-          "frame.preview_sha256",
-        ) ?? (() => {
-          throw new DatasetGatewayContractError("frame.preview_sha256 отсутствует");
-        })(),
-        previewAvailable: (() => {
-          if (admittedFrame.preview_available !== true) {
-            throw new DatasetGatewayContractError(
-              "frame.preview_available: ожидался true",
-            );
-          }
-          return true as const;
-        })(),
-      }
-    : null;
   const representations = array(
     source.representations,
     "representations",
@@ -366,9 +465,6 @@ export function parseDatasetGatewayCatalog(
   ) {
     throw new DatasetGatewayContractError("Vendor-map boundary завышен");
   }
-  if (dataset.frame_semantics !== "one-lidar-revolution") {
-    throw new DatasetGatewayContractError("GOOSE frame semantics несовместима");
-  }
   return {
     storage: {
       configured: boolean(storage.configured, "storage.configured"),
@@ -382,23 +478,7 @@ export function parseDatasetGatewayCatalog(
       ),
       requiredWslRoot: string(storage.required_wsl_root, "storage.required_wsl_root"),
     },
-    source: {
-      sourceId: string(dataset.source_id, "source_id", true),
-      displayName: string(dataset.display_name, "display_name"),
-      role: string(dataset.role, "role", true),
-      license: string(dataset.license, "license"),
-      format: string(dataset.format, "format", true),
-      frameSemantics: "one-lidar-revolution",
-      platforms: displayStrings(dataset.platforms, "platforms"),
-      superclasses: strings(dataset.superclasses, "superclasses"),
-      validationArchiveGb: number(
-        download.validation_archive_gb,
-        "validation_archive_gb",
-      ),
-      admissionStatus,
-      archive: archiveValue,
-      frame: frameValue,
-    },
+    sources: parsedSources,
     representations,
     pipeline,
     currentInput: {
@@ -417,9 +497,12 @@ export function parseDatasetNativeScanPreview(
   value: unknown,
 ): DatasetNativeScanPreview {
   const source = record(value, "Dataset preview");
+  const isGoose = source.schema_version === "missioncore.dataset-native-scan-preview/v1"
+    && source.source_id === "goose-3d/v2025-08-22";
+  const isRellis = source.schema_version === "missioncore.dataset-native-scan-preview/v2"
+    && source.source_id === "rellis-3d/v1.1";
   if (
-    source.schema_version !== "missioncore.dataset-native-scan-preview/v1"
-    || source.source_id !== "goose-3d/v2025-08-22"
+    (!isGoose && !isRellis)
     || source.representation !== "native-scan"
     || source.sampling !== "deterministic-even-index"
   ) {
@@ -463,6 +546,9 @@ export function parseDatasetNativeScanPreview(
     "ground_truth_ground",
     1,
   );
+  const evaluationMask = isRellis
+    ? integers(source.evaluation_mask, "evaluation_mask", 1)
+    : Array.from({ length: pointCount }, () => 1);
   if (
     pointCount < 1
     || pointCount > 50_000
@@ -472,35 +558,74 @@ export function parseDatasetNativeScanPreview(
     || semanticLabelIds.length !== pointCount
     || semanticRgb0To255.length !== pointCount * 3
     || groundTruthGround.length !== pointCount
+    || evaluationMask.length !== pointCount
   ) {
     throw new DatasetGatewayContractError("Dataset preview arrays не выровнены");
   }
   const classes = array(source.classes, "classes").map((value, index) => {
     const item = record(value, `classes[${index}]`);
+    const groundTarget = item.ground_target;
+    if (
+      groundTarget !== undefined
+      && groundTarget !== "ground"
+      && groundTarget !== "non-ground"
+      && groundTarget !== "ignore"
+    ) {
+      throw new DatasetGatewayContractError("class.ground_target неизвестен");
+    }
+    const normalizedGroundTarget: "ground" | "non-ground" | "ignore" | null =
+      groundTarget === undefined ? null : groundTarget;
     return {
       labelId: number(item.label_id, "class.label_id"),
       className: string(item.class_name, "class.class_name", true),
       hex: string(item.hex, "class.hex"),
-      challengeCategoryId: number(
-        item.challenge_category_id,
-        "class.challenge_category_id",
-      ),
-      challengeCategoryName: string(
-        item.challenge_category_name,
-        "class.challenge_category_name",
-        true,
-      ),
+      challengeCategoryId: item.challenge_category_id === undefined
+        ? null
+        : number(item.challenge_category_id, "class.challenge_category_id"),
+      challengeCategoryName: item.challenge_category_name === undefined
+        ? null
+        : string(
+            item.challenge_category_name,
+            "class.challenge_category_name",
+            true,
+          ),
+      groundTarget: normalizedGroundTarget,
+      sourcePointCount: item.source_point_count === undefined
+        ? null
+        : number(item.source_point_count, "class.source_point_count"),
     };
   });
   const safety = record(source.safety, "safety");
   if (
     safety.visualization_only !== true
     || safety.navigation_or_safety_accepted !== false
+    || (isRellis && safety.compatibility_smoke_only !== true)
   ) {
     throw new DatasetGatewayContractError("Dataset preview safety boundary нарушен");
   }
+  const coordinateFrame = isRellis
+    ? (() => {
+        const frame = record(source.coordinate_frame, "coordinate_frame");
+        if (
+          frame.frame_id !== "sensor/lidar/os1"
+          || frame.x !== "forward"
+          || frame.y !== "left"
+          || frame.z !== "up"
+          || frame.handedness !== "right"
+          || frame.transform_applied !== false
+        ) {
+          throw new DatasetGatewayContractError("RELLIS coordinate frame несовместим");
+        }
+        return {
+          frameId: "sensor/lidar/os1",
+          x: "forward" as const,
+          y: "left" as const,
+          z: "up" as const,
+        };
+      })()
+    : null;
   return {
-    sourceId: "goose-3d/v2025-08-22",
+    sourceId: isRellis ? "rellis-3d/v1.1" : "goose-3d/v2025-08-22",
     frameId: string(source.frame_id, "frame_id", true),
     sourcePointCount,
     pointCount,
@@ -509,7 +634,10 @@ export function parseDatasetNativeScanPreview(
     semanticLabelIds,
     semanticRgb0To255,
     groundTruthGround,
+    evaluationMask,
     classes,
+    coordinateFrame,
+    compatibilitySmokeOnly: isRellis,
   };
 }
 
@@ -711,14 +839,22 @@ export async function fetchDatasetGatewayCatalog(
 }
 
 export async function fetchDatasetNativeScanPreview(
-  options: { signal?: AbortSignal; fetcher?: DatasetFetch } = {},
+  options: {
+    sourceId?: DatasetNativeScanPreview["sourceId"];
+    signal?: AbortSignal;
+    fetcher?: DatasetFetch;
+  } = {},
 ): Promise<DatasetNativeScanPreview> {
   const fetcher = options.fetcher ?? fetch;
-  const response = await fetcher("/api/v1/lidar/dataset-gateway/preview", {
+  const sourceId = options.sourceId ?? "goose-3d/v2025-08-22";
+  const response = await fetcher(
+    `/api/v1/lidar/dataset-gateway/preview?source_id=${encodeURIComponent(sourceId)}`,
+    {
     method: "GET",
     headers: { Accept: "application/json" },
     signal: options.signal,
-  });
+    },
+  );
   return parseDatasetNativeScanPreview(await responseJson(response));
 }
 

apps/control-station/src/styles/responsive.css

@@ -224,7 +224,9 @@
   }
 
   .dataset-fragment-comparison,
-  .dataset-fragment-risks {
+  .dataset-fragment-risks,
+  .rellis-review__metrics,
+  .rellis-review__policy > div {
     grid-template-columns: 1fr;
   }
 

apps/control-station/src/styles/workspaces.css

@@ -1223,6 +1223,85 @@
   line-height: 1.5;
 }
 
+.rellis-review__metrics {
+  display: grid;
+  grid-template-columns: repeat(3, minmax(0, 1fr));
+  gap: 0.35rem;
+}
+
+.rellis-review__metrics article {
+  display: grid;
+  gap: 0.2rem;
+  border-radius: 0.85rem;
+  background: var(--station-panel);
+  padding: 0.78rem 0.85rem;
+}
+
+.rellis-review__metrics span,
+.rellis-review__metrics small {
+  color: var(--nodedc-text-muted);
+  font-size: 0.55rem;
+}
+
+.rellis-review__metrics strong {
+  color: var(--nodedc-text-primary);
+  font-size: 1.05rem;
+}
+
+.rellis-review__policy {
+  display: grid;
+  gap: 0.7rem;
+  border-radius: 1rem;
+  background: var(--station-panel);
+  padding: 0.9rem 1rem;
+}
+
+.rellis-review__policy h3,
+.rellis-review__policy p {
+  margin: 0;
+}
+
+.rellis-review__policy h3 {
+  margin-top: 0.28rem;
+  color: var(--nodedc-text-primary);
+  font-size: 0.95rem;
+}
+
+.rellis-review__policy p {
+  max-width: 52rem;
+  margin-top: 0.3rem;
+  color: var(--nodedc-text-muted);
+  font-size: 0.6rem;
+  line-height: 1.5;
+}
+
+.rellis-review__policy > div {
+  display: grid;
+  grid-template-columns: repeat(3, minmax(0, 1fr));
+  gap: 0.35rem;
+}
+
+.rellis-review__policy article {
+  display: grid;
+  align-content: start;
+  gap: 0.35rem;
+  border-radius: 0.75rem;
+  background: rgb(255 255 255 / 0.03);
+  padding: 0.7rem 0.75rem;
+}
+
+.rellis-review__policy article span {
+  color: var(--nodedc-text-muted);
+  font-size: 0.54rem;
+}
+
+.rellis-review__policy article strong {
+  color: var(--nodedc-text-secondary);
+  font-size: 0.62rem;
+  font-weight: 560;
+  line-height: 1.5;
+}
+
 .dataset-sequence-timeline {
   height: 2rem;
 }
@@ -2043,6 +2122,11 @@
   font-size: 1rem;
 }
 
+.dataset-library__entries {
+  display: grid;
+  gap: 1rem;
+}
+
 .dataset-entry {
   display: grid;
   grid-template-columns: minmax(20rem, 1.2fr) minmax(22rem, 0.8fr);

apps/control-station/src/workspaces/DatasetGatewayWorkspace.tsx

@@ -8,12 +8,15 @@ import {
 import {
   fetchDatasetGatewayCatalog,
   type DatasetGatewayCatalog,
+  type DatasetSource,
+  type DatasetSourceAdmissionStatus,
 } from "../core/lidar/datasetGateway";
 import {
   fetchPolygonRunCatalog,
   type PolygonRunCatalog,
 } from "../core/polygon/runArchive";
 import { GooseDatasetReview } from "./GooseDatasetReview";
+import { RellisDatasetReview } from "./RellisDatasetReview";
 
 const representationLabels: Record<string, string> = {
   "native-scan": "Исходный скан",
@@ -27,15 +30,17 @@ function errorMessage(error: unknown): string {
     : "Каталог датасетов недоступен.";
 }
 
-function admissionLabel(status: DatasetGatewayCatalog["source"]["admissionStatus"]) {
-  const labels: Record<typeof status, string> = {
+function admissionLabel(status: DatasetSourceAdmissionStatus): string {
+  const labels: Record<DatasetSourceAdmissionStatus, string> = {
     "blocked-storage-policy": "Worker не настроен",
     "ready-for-download": "Готов к загрузке",
+    "ready-for-smoke": "Готов к smoke",
     downloading: "Загружается",
     downloaded: "Загружен",
     verifying: "Проверяется",
     verified: "Проверен",
-    "frame-ready": "Первый кадр готов",
+    "frame-ready": "Dataset готов",
+    "smoke-ready": "Smoke готов",
   };
   return labels[status];
 }
@@ -55,12 +60,42 @@ function isGooseQualificationRun(
     && item.scenarioGeneration.startsWith("goose-3d");
 }
 
+function sourceReady(source: DatasetSource): boolean {
+  return source.admissionStatus === "frame-ready"
+    || source.admissionStatus === "smoke-ready";
+}
+
+function sourceDescription(source: DatasetSource): string {
+  if (source.sourceKind === "goose") {
+    return "Восемь фрагментов и 961 разреженный размеченный оборот VLS-128. Здесь уже опубликовано покадровое сравнение текущего ground baseline и Patchwork++.";
+  }
+  return "Независимый off-road источник с Ouster OS1 64. Сейчас открыт официальный frame 000104 для проверки reader, осей, ontology и ground-policy; полный benchmark ещё не выполнялся.";
+}
+
+function sourceFooter(source: DatasetSource, storageReady: boolean): string {
+  if (source.admissionStatus === "frame-ready") {
+    return "Native scans и разметка приняты. Можно открыть фрагменты и результаты алгоритмов.";
+  }
+  if (source.admissionStatus === "smoke-ready") {
+    return "Официальный пример совместим. Можно проверить scan, классы и ground mapping.";
+  }
+  if (source.admissionStatus === "downloading") {
+    return "Архив остаётся на D worker; после загрузки проверяются digest, лицензия и point-label alignment.";
+  }
+  if (!storageReady) {
+    return "Сначала нужен допущенный Dataset Root на диске D worker.";
+  }
+  return source.sourceKind === "rellis"
+    ? "Следующий шаг: пропустить официальный 24 МБ example через smoke admission."
+    : "Следующий шаг: загрузить validation archive на worker и проверить hash/license.";
+}
+
 export function DatasetGatewayWorkspace() {
   const [catalog, setCatalog] = useState<DatasetGatewayCatalog | null>(null);
   const [loading, setLoading] = useState(true);
   const [error, setError] = useState<string | null>(null);
   const [reloadGeneration, setReloadGeneration] = useState(0);
-  const [previewOpen, setPreviewOpen] = useState(false);
+  const [openSourceId, setOpenSourceId] = useState<string | null>(null);
   const [runCatalog, setRunCatalog] = useState<PolygonRunCatalog | null>(null);
   const [selectedRunId, setSelectedRunId] = useState<string | null>(null);
   const [runError, setRunError] = useState<string | null>(null);
@@ -85,7 +120,9 @@ export function DatasetGatewayWorkspace() {
   }, [reloadGeneration]);
 
   useEffect(() => {
-    if (catalog?.source.admissionStatus !== "downloading") return;
+    if (!catalog?.sources.some((source) => source.admissionStatus === "downloading")) {
+      return;
+    }
     const timer = window.setTimeout(
       () => setReloadGeneration((value) => value + 1),
       5_000,
@@ -113,10 +150,10 @@ export function DatasetGatewayWorkspace() {
     return () => controller.abort();
   }, []);
 
-  const downloadProgress = catalog?.source.archive
-    ? catalog.source.archive.bytesTransferred / catalog.source.archive.totalBytes
-    : null;
   const gooseRuns = runCatalog?.items.filter(isGooseQualificationRun) ?? [];
+  const openSource = catalog?.sources.find(
+    (source) => source.sourceId === openSourceId,
+  ) ?? null;
 
   return (
     <div className="standard-workspace dataset-workspace">
@@ -125,17 +162,17 @@ export function DatasetGatewayWorkspace() {
           <span className="section-eyebrow">ЗАЧЕМ ЭТО НУЖНО</span>
           <h2>Независимая проверка алгоритмов</h2>
           <p>
-            Датасет содержит известные размеченные данные. Мы показываем
-            конкретный фрагмент, результаты каждого алгоритма и ошибки
-            относительно разметки. Он не подмешивается в диагностику реального
-            сенсора и не заменяет closed-loop симуляцию.
+            Каждый источник остаётся отдельным: собственные sensor domain,
+            разметка, лицензия и результаты. Совпадение результата на GOOSE и
+            RELLIS снижает риск подгонки под один датасет, но не заменяет replay
+            реального сенсора и closed-loop симуляцию.
           </p>
         </div>
         <ol aria-label="Как использовать датасет">
-          <li><span>01</span>Выбрать фрагмент</li>
-          <li><span>02</span>Посмотреть сканы</li>
+          <li><span>01</span>Выбрать источник</li>
+          <li><span>02</span>Проверить scan и labels</li>
           <li><span>03</span>Сравнить алгоритмы</li>
-          <li><span>04</span>Проверить риски</li>
+          <li><span>04</span>Проверить переносимость</li>
         </ol>
       </section>
 
@@ -171,80 +208,91 @@ export function DatasetGatewayWorkspace() {
               </StatusBadge>
             </header>
 
-            <article className="dataset-entry">
-              <div className="dataset-entry__identity">
-                <span className="dataset-entry__mark">G</span>
-                <div>
-                  <span>PUBLIC · OFF-ROAD · LABELED</span>
-                  <h3>{catalog.source.displayName}</h3>
-                  <p>
-                    Validation split: восемь фрагментов исходных записей и 961
-                    разреженный размеченный оборот VLS-128. Это коллекция native
-                    scans для perception, а не непрерывное видео или траектория
-                    машины.
-                  </p>
-                </div>
-              </div>
-              <dl>
-                <div>
-                  <dt>Состояние</dt>
-                  <dd>{admissionLabel(catalog.source.admissionStatus)}</dd>
-                </div>
-                <div>
-                  <dt>Validation</dt>
-                  <dd>{catalog.source.validationArchiveGb} ГБ</dd>
-                </div>
-                <div>
-                  <dt>Группы</dt>
-                  <dd>{catalog.source.superclasses.length} superclass</dd>
-                </div>
-                <div>
-                  <dt>Лицензия</dt>
-                  <dd>{catalog.source.license}</dd>
-                </div>
-              </dl>
-              {catalog.source.admissionStatus === "downloading"
-              && catalog.source.archive
-              && downloadProgress !== null ? (
-                <div className="dataset-download" aria-label="Загрузка GOOSE validation">
-                  <span style={{ width: `${downloadProgress * 100}%` }} />
-                  <p>
-                    {formatBytes(catalog.source.archive.bytesTransferred)}
-                    {" из "}
-                    {formatBytes(catalog.source.archive.totalBytes)}
-                  </p>
-                </div>
-              ) : null}
-              <footer>
-                <p>
-                  {catalog.source.admissionStatus === "frame-ready"
-                    ? "Native scan и разметка прошли admission. Можно открыть независимый ground truth."
-                    : catalog.source.admissionStatus === "downloading"
-                      ? "Архив остаётся на D worker. После загрузки проверим ZIP, лицензию, digest и point-label alignment."
-                      : catalog.storage.admitted
-                        ? "Следующий шаг: загрузить validation archive на worker и проверить hash/license."
-                        : "Сначала нужно допустить Dataset Root на диске D worker. Сейчас открывать нечего."}
-                </p>
-                <div>
-                  <Button
-                    size="compact"
-                    variant="secondary"
-                    disabled={catalog.source.admissionStatus !== "frame-ready"}
-                    title={
-                      catalog.source.admissionStatus === "frame-ready"
-                        ? "Открыть фрагменты, сканы и результаты анализа"
-                        : "Размеченные сканы ещё не импортированы"
-                    }
-                    onClick={() => setPreviewOpen((value) => !value)}
+            <div className="dataset-library__entries">
+              {catalog.sources.map((source) => {
+                const downloadProgress = source.archive
+                  ? source.archive.bytesTransferred / source.archive.totalBytes
+                  : null;
+                const opened = source.sourceId === openSourceId;
+                return (
+                  <article
+                    className="dataset-entry"
+                    data-source={source.sourceKind}
+                    key={source.sourceId}
                   >
-                    {previewOpen ? "Закрыть датасет" : "Открыть датасет"}
-                  </Button>
-                </div>
-              </footer>
-            </article>
+                    <div className="dataset-entry__identity">
+                      <span className="dataset-entry__mark">
+                        {source.sourceKind === "goose" ? "G" : "R"}
+                      </span>
+                      <div>
+                        <span>
+                          PUBLIC · OFF-ROAD · LABELED
+                          {source.sourceKind === "rellis" ? " · RESEARCH" : ""}
+                        </span>
+                        <h3>{source.displayName}</h3>
+                        <p>{sourceDescription(source)}</p>
+                      </div>
+                    </div>
+                    <dl>
+                      <div>
+                        <dt>Состояние</dt>
+                        <dd>{admissionLabel(source.admissionStatus)}</dd>
+                      </div>
+                      <div>
+                        <dt>Сканер</dt>
+                        <dd>{source.sensor}</dd>
+                      </div>
+                      <div>
+                        <dt>Размеченных сканов</dt>
+                        <dd>{source.annotatedScanCount.toLocaleString("ru-RU")}</dd>
+                      </div>
+                      <div>
+                        <dt>Лицензия</dt>
+                        <dd>{source.license}</dd>
+                      </div>
+                    </dl>
+                    {source.admissionStatus === "downloading"
+                    && source.archive
+                    && downloadProgress !== null ? (
+                      <div
+                        className="dataset-download"
+                        aria-label={`Загрузка ${source.displayName}`}
+                      >
+                        <span style={{ width: `${downloadProgress * 100}%` }} />
+                        <p>
+                          {formatBytes(source.archive.bytesTransferred)}
+                          {" из "}
+                          {formatBytes(source.archive.totalBytes)}
+                        </p>
+                      </div>
+                    ) : null}
+                    <footer>
+                      <p>{sourceFooter(source, catalog.storage.admitted)}</p>
+                      <div>
+                        <Button
+                          size="compact"
+                          variant="secondary"
+                          disabled={!sourceReady(source)}
+                          title={
+                            sourceReady(source)
+                              ? "Открыть содержимое источника"
+                              : "Совместимый preview ещё не опубликован"
+                          }
+                          onClick={() => setOpenSourceId(
+                            opened ? null : source.sourceId,
+                          )}
+                        >
+                          {opened ? "Закрыть датасет" : "Открыть датасет"}
+                        </Button>
+                      </div>
+                    </footer>
+                  </article>
+                );
+              })}
+            </div>
           </GlassSurface>
 
-          {previewOpen && selectedRunId ? (
+          {openSource?.sourceKind === "goose" && selectedRunId ? (
             <>
               {gooseRuns.length > 1 ? (
                 <div className="dataset-result-select">
@@ -267,12 +315,14 @@ export function DatasetGatewayWorkspace() {
               ) : null}
               <GooseDatasetReview runId={selectedRunId} />
             </>
-          ) : previewOpen ? (
+          ) : openSource?.sourceKind === "goose" ? (
             <section className="polygon-review-unavailable">
               <StatusBadge tone="warning">Review недоступен</StatusBadge>
-              <h3>Датасет принят, но результаты анализа не опубликованы</h3>
+              <h3>GOOSE принят, но анализ не опубликован</h3>
               <p>{runError ?? "Нет совместимой версии покадрового анализа."}</p>
             </section>
+          ) : openSource?.sourceKind === "rellis" ? (
+            <RellisDatasetReview />
           ) : null}
 
           <details className="dataset-contract">

apps/control-station/src/workspaces/LidarGroundPointCloud.tsx

@@ -24,6 +24,7 @@ export interface LidarGroundPointCloudFrame {
     disagreement: number[];
     candidateDisagreement?: number[];
     groundTruthGround?: number[];
+    evaluationMask?: number[];
   };
 }
 
@@ -87,13 +88,18 @@ function frameColors(
       );
     } else if (mode === "ground-truth") {
       const groundTruth = frame.masks.groundTruthGround?.[index] === 1;
-      setRgb(
-        colors,
-        offset,
-        groundTruth ? 0.76 : 0.29,
-        groundTruth ? 0.86 : 0.33,
-        groundTruth ? 0.52 : 0.36,
-      );
+      const evaluated = frame.masks.evaluationMask?.[index] !== 0;
+      if (!evaluated) {
+        setRgb(colors, offset, 0.86, 0.61, 0.24);
+      } else {
+        setRgb(
+          colors,
+          offset,
+          groundTruth ? 0.76 : 0.29,
+          groundTruth ? 0.86 : 0.33,
+          groundTruth ? 0.52 : 0.36,
+        );
+      }
     } else if (mode === "current") {
       setRgb(
         colors,

apps/control-station/src/workspaces/RellisDatasetReview.tsx

@@ -0,0 +1,239 @@
+import { useEffect, useMemo, useState } from "react";
+import { StatusBadge } from "@nodedc/ui-react";
+
+import {
+  fetchDatasetNativeScanPreview,
+  type DatasetNativeScanPreview,
+} from "../core/lidar/datasetGateway";
+import {
+  LidarGroundPointCloud,
+  type LidarGroundViewMode,
+} from "./LidarGroundPointCloud";
+
+const modes: ReadonlyArray<[LidarGroundViewMode, string]> = [
+  ["intensity", "Исходный скан"],
+  ["semantic", "Классы RELLIS"],
+  ["ground-truth", "Ground target"],
+];
+
+function formatPercent(value: number): string {
+  return new Intl.NumberFormat("ru-RU", {
+    style: "percent",
+    maximumFractionDigits: 1,
+  }).format(value);
+}
+
+function errorMessage(error: unknown): string {
+  return error instanceof Error && error.message.trim()
+    ? error.message
+    : "Официальный пример RELLIS недоступен.";
+}
+
+function modeExplanation(mode: LidarGroundViewMode): string {
+  if (mode === "semantic") {
+    return "Цвета из закреплённой официальной ontology RELLIS-3D.";
+  }
+  if (mode === "ground-truth") {
+    return "Зелёный — ground, серый — non-ground, янтарный — ignore.";
+  }
+  return "Один исходный оборот Ouster OS1 64; цвет — нормализованная remission.";
+}
+
+export function RellisDatasetReview() {
+  const [preview, setPreview] = useState<DatasetNativeScanPreview | null>(null);
+  const [error, setError] = useState<string | null>(null);
+  const [mode, setMode] = useState<LidarGroundViewMode>("semantic");
+
+  useEffect(() => {
+    const controller = new AbortController();
+    setError(null);
+    void fetchDatasetNativeScanPreview({
+      sourceId: "rellis-3d/v1.1",
+      signal: controller.signal,
+    })
+      .then((value) => {
+        if (!controller.signal.aborted) setPreview(value);
+      })
+      .catch((loadError: unknown) => {
+        if (!controller.signal.aborted) setError(errorMessage(loadError));
+      });
+    return () => controller.abort();
+  }, []);
+
+  const scene = useMemo(() => {
+    if (!preview) return null;
+    const empty = Array.from({ length: preview.pointCount }, () => 0);
+    return {
+      pointCount: preview.pointCount,
+      pointsXyzM: preview.pointsXyzM,
+      intensity0To255: preview.remission0To255,
+      semanticRgb0To255: preview.semanticRgb0To255,
+      masks: {
+        currentGround: empty,
+        currentAssigned: preview.evaluationMask,
+        candidateGround: empty,
+        candidateAssigned: preview.evaluationMask,
+        disagreement: empty,
+        groundTruthGround: preview.groundTruthGround,
+        evaluationMask: preview.evaluationMask,
+      },
+    };
+  }, [preview]);
+
+  if (error) {
+    return (
+      <section className="polygon-review-unavailable">
+        <StatusBadge tone="danger">Smoke preview недоступен</StatusBadge>
+        <h3>RELLIS-3D не открыт</h3>
+        <p>{error}</p>
+      </section>
+    );
+  }
+
+  if (!preview || !scene) {
+    return (
+      <section className="polygon-review-unavailable">
+        <StatusBadge tone="accent">Проверяем пример</StatusBadge>
+        <h3>Открываем официальный RELLIS scan</h3>
+        <p>Исходные dataset bytes не переносятся в браузер.</p>
+      </section>
+    );
+  }
+
+  const evaluatedPoints = preview.evaluationMask.reduce(
+    (total, value) => total + value,
+    0,
+  );
+  const groundPoints = preview.groundTruthGround.reduce(
+    (total, value, index) => total + value * (preview.evaluationMask[index] ?? 0),
+    0,
+  );
+  const groundClasses = preview.classes.filter(
+    (item) => item.groundTarget === "ground",
+  );
+  const nonGroundClasses = preview.classes.filter(
+    (item) => item.groundTarget === "non-ground",
+  );
+  const ignoredClasses = preview.classes.filter(
+    (item) => item.groundTarget === "ignore",
+  );
+
+  return (
+    <section
+      className="dataset-sequence-review rellis-review"
+      aria-label="Просмотр официального примера RELLIS-3D"
+    >
+      <header className="dataset-sequence-review__truth">
+        <div>
+          <span className="section-eyebrow">RELLIS S0 · COMPATIBILITY SMOKE</span>
+          <h2>Официальный Ouster scan читается без конвертации формата</h2>
+          <p>
+            Frame {preview.frameId}: исходные XYZI и point-wise labels остались
+            выровнены. Это проверка reader, осей, цветов и ground-policy — ещё не
+            сравнение алгоритмов и не основание для навигации.
+          </p>
+        </div>
+        <dl>
+          <div>
+            <dt>Исходных точек</dt>
+            <dd>{preview.sourcePointCount.toLocaleString("ru-RU")}</dd>
+          </div>
+          <div>
+            <dt>Browser preview</dt>
+            <dd>{preview.pointCount.toLocaleString("ru-RU")}</dd>
+          </div>
+          <div>
+            <dt>Sensor frame</dt>
+            <dd>{preview.coordinateFrame?.frameId ?? "—"}</dd>
+          </div>
+        </dl>
+      </header>
+
+      <section className="polygon-review-player">
+        <header className="polygon-review-player__header">
+          <div>
+            <span className="section-eyebrow">OFFICIAL EXAMPLE · FRAME 000104</span>
+            <strong>Ouster OS1 64 · X forward · Y left · Z up</strong>
+          </div>
+          <div className="polygon-review-mode" aria-label="Режим RELLIS preview">
+            {modes.map(([viewMode, label]) => (
+              <button
+                type="button"
+                key={viewMode}
+                data-active={mode === viewMode ? "true" : undefined}
+                onClick={() => setMode(viewMode)}
+              >
+                {label}
+              </button>
+            ))}
+          </div>
+        </header>
+        <div className="polygon-review-stage">
+          <LidarGroundPointCloud
+            frame={scene}
+            mode={mode}
+            coordinateFrame="sensor-fixed"
+          />
+          <div className="polygon-review-stage__legend">
+            <strong>{modes.find(([viewMode]) => viewMode === mode)?.[1]}</strong>
+            <span>{modeExplanation(mode)}</span>
+          </div>
+        </div>
+      </section>
+
+      <div className="rellis-review__metrics">
+        <article>
+          <span>Оценимых точек preview</span>
+          <strong>{formatPercent(evaluatedPoints / preview.pointCount)}</strong>
+          <small>ignore не участвует в метриках</small>
+        </article>
+        <article>
+          <span>Ground среди оценимых</span>
+          <strong>
+            {formatPercent(evaluatedPoints ? groundPoints / evaluatedPoints : 0)}
+          </strong>
+          <small>версионная mapping policy v1</small>
+        </article>
+        <article>
+          <span>Классов в этом scan</span>
+          <strong>{preview.classes.length}</strong>
+          <small>из 20 классов ontology</small>
+        </article>
+      </div>
+
+      <section className="rellis-review__policy" aria-label="Ground target mapping">
+        <header>
+          <span className="section-eyebrow">GROUND TARGET POLICY V1</span>
+          <h3>Что именно будет оцениваться</h3>
+          <p>
+            Mapping принадлежит Mission Core и версионируется отдельно от
+            ontology датасета. Вода, лужи, void, sky и неопределённый object не
+            засчитываются ни как ground, ни как obstacle.
+          </p>
+        </header>
+        <div>
+          <article>
+            <span>Ground</span>
+            <strong>{groundClasses.map((item) => item.className).join(" · ") || "—"}</strong>
+          </article>
+          <article>
+            <span>Non-ground</span>
+            <strong>
+              {nonGroundClasses.map((item) => item.className).join(" · ") || "—"}
+            </strong>
+          </article>
+          <article>
+            <span>Ignore</span>
+            <strong>{ignoredClasses.map((item) => item.className).join(" · ") || "—"}</strong>
+          </article>
+        </div>
+      </section>
+
+      <p className="dataset-sequence-review__raw-note">
+        Лицензия RELLIS-3D — CC-BY-NC-SA-3.0: источник годится для независимой
+        исследовательской проверки, но коммерческое использование данных или
+        производных моделей требует отдельного лицензионного решения.
+      </p>
+    </section>
+  );
+}

apps/control-station/test/datasetGateway.test.mjs

@@ -35,7 +35,7 @@ after(async () => {
 
 function catalog(overrides = {}) {
   return {
-    schema_version: "missioncore.dataset-gateway-catalog/v2",
+    schema_version: "missioncore.dataset-gateway-catalog/v3",
     access: "read-only",
     storage: {
       configured: false,
@@ -49,19 +49,60 @@ function catalog(overrides = {}) {
     },
     sources: [{
       source_id: "goose-3d/v2025-08-22",
+      source_kind: "goose",
       display_name: "GOOSE 3D",
       role: "primary-offroad-semantic-baseline",
       license: "CC-BY-SA-4.0",
+      commercial_use: "allowed-with-share-alike",
       format: "semantickitti-xyzi-label",
       frame_semantics: "one-lidar-revolution",
+      sensor: "VLS-128",
       platforms: ["MuCAR-3", "ALICE", "Spot"],
       annotations: ["semantic-point", "instance-point"],
       superclasses: ["natural-ground", "obstacle"],
       download: {
         automatic: false,
         reason: "operator-admitted-large-artifact-only",
+        smoke_example_mb: null,
+        primary_scan_archive_gb: 3.3,
+        label_archive_gb: null,
+        poses_archive_gb: null,
         validation_archive_gb: 3.3,
       },
+      statistics: {
+        fragment_count: 8,
+        annotated_scan_count: 961,
+      },
+      admission: {
+        status: "blocked-storage-policy",
+        archive: null,
+        frame: null,
+      },
+    }, {
+      source_id: "rellis-3d/v1.1",
+      source_kind: "rellis",
+      display_name: "RELLIS-3D",
+      role: "independent-offroad-cross-dataset-check",
+      license: "CC-BY-NC-SA-3.0",
+      commercial_use: "research-only-license-review-required",
+      format: "semantickitti-xyzi-label",
+      frame_semantics: "one-lidar-revolution",
+      sensor: "Ouster OS1 64",
+      platforms: ["Clearpath Warthog"],
+      annotations: ["semantic-point"],
+      superclasses: ["ground", "obstacle", "ignore"],
+      download: {
+        automatic: false,
+        reason: "operator-admitted-large-artifact-only",
+        smoke_example_mb: 24,
+        primary_scan_archive_gb: 14,
+        label_archive_gb: 0.174,
+        poses_archive_gb: 0.174,
+      },
+      statistics: {
+        fragment_count: 5,
+        annotated_scan_count: 13_556,
+      },
       admission: {
         status: "blocked-storage-policy",
         archive: null,
@@ -115,7 +156,8 @@ test("parses three distinct LiDAR representations and current-input boundary", (
   );
   assert.equal(parsed.representations[2].accumulation, true);
   assert.equal(parsed.currentInput.admittedForPatchworkpp, false);
-  assert.equal(parsed.source.frameSemantics, "one-lidar-revolution");
+  assert.equal(parsed.sources[0].frameSemantics, "one-lidar-revolution");
+  assert.equal(parsed.sources[1].sourceKind, "rellis");
 });
 
 test("rejects path exposure and upgraded K1 semantics", () => {
@@ -147,7 +189,7 @@ test("fetches the read-only gateway endpoint", async () => {
   });
   assert.equal(calls[0].url, "/api/v1/lidar/dataset-gateway");
   assert.equal(calls[0].init.method, "GET");
-  assert.equal(parsed.source.displayName, "GOOSE 3D");
+  assert.equal(parsed.sources[0].displayName, "GOOSE 3D");
 });
 
 test("decodes one bounded point-aligned native-scan preview", async () => {
@@ -182,10 +224,19 @@ test("decodes one bounded point-aligned native-scan preview", async () => {
   assert.equal(parsed.pointCount, 2);
   assert.deepEqual(parsed.groundTruthGround, [1, 0]);
 
+  let requestedUrl = null;
   const fetched = await fetchDatasetNativeScanPreview({
-    fetcher: async () => new Response(JSON.stringify(payload), { status: 200 }),
+    fetcher: async (url) => {
+      requestedUrl = url;
+      return new Response(JSON.stringify(payload), { status: 200 });
+    },
   });
   assert.equal(fetched.frameId, "frame-1");
+  assert.deepEqual(fetched.evaluationMask, [1, 1]);
+  assert.equal(
+    requestedUrl,
+    "/api/v1/lidar/dataset-gateway/preview?source_id=goose-3d%2Fv2025-08-22",
+  );
 
   payload.semantic_rgb_0_to_255.pop();
   assert.throws(
@@ -194,6 +245,92 @@ test("decodes one bounded point-aligned native-scan preview", async () => {
   );
 });
 
+test("decodes the RELLIS compatibility smoke with explicit ignore mask", async () => {
+  const payload = {
+    schema_version: "missioncore.dataset-native-scan-preview/v2",
+    source_id: "rellis-3d/v1.1",
+    frame_id: "000104",
+    representation: "native-scan",
+    sampling: "deterministic-even-index",
+    source_point_count: 3,
+    point_count: 3,
+    points_xyz_m: [[1, 2, 3], [4, 5, 6], [7, 8, 9]],
+    remission_0_to_255: [0, 127, 255],
+    semantic_label_ids: [3, 4, 31],
+    semantic_rgb_0_to_255: [0, 102, 0, 0, 255, 0, 239, 255, 134],
+    ground_truth_ground: [1, 0, 0],
+    evaluation_mask: [1, 1, 0],
+    classes: [
+      {
+        label_id: 3,
+        class_name: "grass",
+        hex: "#006600",
+        ground_target: "ground",
+        source_point_count: 1,
+      },
+      {
+        label_id: 4,
+        class_name: "tree",
+        hex: "#00ff00",
+        ground_target: "non-ground",
+        source_point_count: 1,
+      },
+      {
+        label_id: 31,
+        class_name: "puddle",
+        hex: "#efff86",
+        ground_target: "ignore",
+        source_point_count: 1,
+      },
+    ],
+    coordinate_frame: {
+      frame_id: "sensor/lidar/os1",
+      handedness: "right",
+      x: "forward",
+      y: "left",
+      z: "up",
+      transform_applied: false,
+    },
+    ground_policy: {
+      schema_version: "missioncore.rellis-ground-target-policy/v1",
+      ground: ["grass"],
+      non_ground: ["tree"],
+      ignore: ["puddle"],
+    },
+    source_evidence: {
+      repository_url: "https://github.com/unmannedlab/RELLIS-3D",
+      repository_commit: "c17a118fcaed1559f03cc32cc3a91dedc557f8b8",
+      label_config_sha256: "5".repeat(64),
+      point_sha256: "e".repeat(64),
+      label_sha256: "9".repeat(64),
+      license: "CC-BY-NC-SA-3.0",
+    },
+    safety: {
+      visualization_only: true,
+      compatibility_smoke_only: true,
+      navigation_or_safety_accepted: false,
+    },
+  };
+  const parsed = parseDatasetNativeScanPreview(payload);
+  assert.equal(parsed.sourceId, "rellis-3d/v1.1");
+  assert.deepEqual(parsed.evaluationMask, [1, 1, 0]);
+  assert.equal(parsed.classes[2].groundTarget, "ignore");
+  assert.equal(parsed.coordinateFrame.frameId, "sensor/lidar/os1");
+
+  let requestedUrl = null;
+  await fetchDatasetNativeScanPreview({
+    sourceId: "rellis-3d/v1.1",
+    fetcher: async (url) => {
+      requestedUrl = url;
+      return new Response(JSON.stringify(payload), { status: 200 });
+    },
+  });
+  assert.equal(
+    requestedUrl,
+    "/api/v1/lidar/dataset-gateway/preview?source_id=rellis-3d%2Fv1.1",
+  );
+});
+
 test("decodes a point-aligned current-vs-Patchwork++ comparison", async () => {
   const payload = {
     schema_version: "missioncore.dataset-ground-comparison-preview/v2",

docs/01_IMPLEMENTATION_PLAN.md

@@ -203,6 +203,14 @@ qualification bootstrap, never the product data plane. A shared
 operator-facing deployment still requires authentication/RBAC, service
 supervision and an accepted routed worker transport.
 
+The Dataset Gateway is now multi-source. RELLIS S0 pins official repository
+frame `000104`, verifies `131,072` Ouster XYZI points against aligned labels and
+publishes a bounded semantic/ground-target preview beside GOOSE in the same
+`Полигон → Датасеты` workflow. This closes only reader, axes, ontology,
+licensing and versioned ignore-policy compatibility. Full RELLIS Ouster scans,
+labels and poses remain D-only admission work before the cross-dataset
+Current/Patchwork++ decision.
+
 Mission Core remains a distributed web product. React is served by a long-lived
 Gateway/API and renders canonical state through browser-native components.
 Gazebo/PX4/ROS 2/Nav2 run headless on a registered Linux simulation worker; the

docs/12_SIMULATION_POLYGON_PRODUCT_AND_SRS.md

@@ -878,6 +878,11 @@ workflow:
 - `Датасеты → Открыть датасет` shows the admitted source. GOOSE validation is
   explicitly grouped into eight independent fragments; Play is bounded to one
   fragment and described as accelerated review of sparse annotated scans.
+- The catalog is multi-source. RELLIS-3D v1.1 appears as an independent Ouster
+  domain with its own license and admission state. Its current `smoke-ready`
+  view shows official frame `000104`, semantic colors, FLU axes and the
+  versioned `ground / non-ground / ignore` mapping; it does not show invented
+  algorithm metrics.
 - The dataset viewer exposes source frame number, nanosecond timestamp gaps,
   ground truth and Current/Patchwork++ overlays.
 - The fixed sensor-centric coordinate frame and operator camera are preserved
@@ -894,6 +899,12 @@ The accepted `3.3 GB` annotated validation ZIP is not a continuous recording.
 Continuous ego-motion requires a separately admitted raw ROS bag and
 localization source.
 
+RELLIS S0 uses only a bounded derivative of the pinned official example for
+browser inspection. The full `14 GB` Ouster SemanticKITTI scans, labels and
+poses remain a separate D-only admission gate. Its `CC-BY-NC-SA-3.0` license
+means cross-dataset research evidence cannot silently become an unrestricted
+commercial runtime or training dependency.
+
 The backend reads the configured repository from
 `MISSIONCORE_POLYGON_RUNS_ROOT` using
 `QualificationRunStore(read_only=True)`. It exposes only:

docs/13_LIDAR_WORKER_PRODUCT_AND_ROADMAP.md

@@ -293,7 +293,7 @@ path. K1 manual review or a new real vehicle dataset is reserved for later
 domain adaptation after a public baseline proves that the pipeline and metric
 harness work.
 
-### L2.5 — Dataset Gateway — first-frame A/B complete
+### L2.5 — Dataset Gateway — GOOSE qualification and RELLIS S0 complete
 
 - [x] Define separate `native-scan`, `normalized-scan` and
   `rolling-local-map` representations.
@@ -317,12 +317,21 @@ harness work.
   through an immutable R1 Polygon replay-shadow run.
 - [x] Add named range/FOV/density/noise/dropout degradation profiles without
   overwriting the native frame.
+- [x] Upgrade the gateway to two independently identified sources instead of
+  treating GOOSE as a universal dataset contract.
+- [x] Pin and verify the official RELLIS-3D Ouster example, preserve its
+  `131,072` point/label alignment and publish a bounded semantic viewer.
+- [x] Version the RELLIS `ground / non-ground / ignore` mapping and expose
+  licensing as research-only evidence.
+- [ ] Admit the full RELLIS Ouster SemanticKITTI scans, labels and poses on
+  worker D, then run the same Current/Patchwork++ harness.
 
 The architectural contract and run sequence are fixed in
 `docs/14_LIDAR_DATASET_GATEWAY.md` and ADR 0021. GOOSE is first because its
 published 3D format is one LiDAR revolution with point-wise semantic and
-instance labels in off-road environments. RELLIS-3D remains the second-source
-cross-check after the GOOSE harness is stable.
+instance labels in off-road environments. The RELLIS-3D compatibility smoke is
+now complete against official frame `000104`; the full second-source algorithm
+cross-check remains the next gate.
 
 ### L3 — LiDAR-native 3D detection
 
@@ -394,7 +403,10 @@ The near-term value is not a prettier point cloud:
 The GOOSE validation-split and deterministic degradation gates are complete:
 pinned Patchwork++ improves micro Ground IoU from `47.42%` to `66.40%`, raises
 natural-ground recall from `51.76%` to `76.22%` and stays below `23.41 ms` p95
-across 961 frames. The decision remains shadow-only. The highest-value
-immediate work is now a second-source cross-check plus LiDAR-native detection
-on the same gateway. Nvblox and alternative SLAM remain later because their
-timing, pose and scan-geometry gates are not yet satisfied.
+across 961 frames. RELLIS S0 proves that the shared reader, axes, ontology and
+ground-target mapping work on a different Ouster off-road domain; it does not
+yet score an algorithm. The decision remains shadow-only. The highest-value
+immediate work is full RELLIS ground qualification, followed by the real
+sensor input contract and LiDAR-native detection on the same gateway. Nvblox
+and alternative SLAM remain later because their timing, pose and scan-geometry
+gates are not yet satisfied.

docs/14_LIDAR_DATASET_GATEWAY.md

@@ -19,12 +19,13 @@ datasets and future real onboard sensors.
 
 Implemented now:
 
-- `missioncore.dataset-gateway-catalog/v2`, exposed read-only at
+- multi-source `missioncore.dataset-gateway-catalog/v3`, exposed read-only at
   `GET /api/v1/lidar/dataset-gateway`;
 - path-free `missioncore.dataset-admission/v1` worker evidence instead of a
   static React status;
-- a bounded `missioncore.dataset-native-scan-preview/v1`, exposed read-only at
-  `GET /api/v1/lidar/dataset-gateway/preview`;
+- bounded `missioncore.dataset-native-scan-preview/v1` (GOOSE) and `/v2`
+  (RELLIS smoke) artifacts, selected by source at
+  `GET /api/v1/lidar/dataset-gateway/preview?source_id=...`;
 - explicit `native-scan`, `normalized-scan` and `rolling-local-map`
   representations;
 - a lossless GOOSE/SemanticKITTI frame reader for little-endian float32 XYZI
@@ -39,6 +40,10 @@ Implemented now:
   `Открыть` action;
 - one admitted GOOSE validation frame with source colors, normalized remission
   and an independent ground-truth view;
+- a pinned RELLIS-3D v1.1 compatibility smoke using the official Ouster example
+  frame `000104`, its native `131,072` XYZI points, point-aligned labels,
+  official ontology colors, explicit FLU sensor axes and a versioned
+  `ground / non-ground / ignore` evaluation policy;
 - a published, dimensioned MuCAR-3/VLS-128 Patchwork++ input profile:
   sensor frame `x-forward / y-left / z-up`, physical height `2.24 m`, native
   one-revolution scan and explicit absence of deskew/full vehicle TF claims;
@@ -54,6 +59,8 @@ Not implemented:
 - no implicit coordinate conversion;
 - no fake ring/timestamp reconstruction for K1 MQTT evidence;
 - no model training or production promotion;
+- no full RELLIS Ouster archive, pose set, algorithm comparison or ROS bag
+  admission yet;
 - no rolling-map implementation yet.
 
 ## Product surface boundary
@@ -73,10 +80,11 @@ The gateway is not part of device quality diagnostics.
   backend evidence contract. They are not a second operator navigation item
   and are not presented as vehicle motion.
 
-Before real dataset bytes exist, the catalog explains the blocked storage gate
-and keeps `Открыть датасет` disabled. It becomes available
-only after the worker manifest says `frame-ready` and the bounded preview passes
-its own point-alignment and safety checks.
+Before compatible source evidence exists, the catalog explains the blocked
+storage gate and keeps `Открыть датасет` disabled. GOOSE becomes available only
+after the worker manifest says `frame-ready`; RELLIS becomes available at
+`smoke-ready` only for the pinned official example. Both bounded previews must
+pass their own identity, point-alignment and safety checks.
 
 ## Why public recordings look different
 
@@ -191,8 +199,53 @@ time; TTL/dynamic filtering prevents stale ghosts.
 - [x] Patchwork++ one-frame accuracy measured against ground truth.
 - [x] Current/Patchwork++ validation-split gate qualified.
 - [x] Sensor-degradation matrix qualified.
+- [x] Dataset catalog accepts more than one independently identified source.
+- [x] Official RELLIS Ouster example passes the shared SemanticKITTI reader.
+- [x] RELLIS axes, ontology colors and versioned ground-target/ignore mapping
+  are visible in the same Dataset workflow.
+- [ ] Full RELLIS Ouster SemanticKITTI scans, labels and poses admitted on
+  worker D.
+- [ ] Current/Patchwork++ RELLIS comparison qualified without obstacle loss.
 - [ ] Rolling local map with pose/TTL/dynamic policy qualified.
 
+## RELLIS S0 compatibility evidence
+
+RELLIS is the independent second-source check, not extra decoration in the
+catalog. GOOSE and RELLIS share the ingress format and viewer, but retain
+separate source identity, sensor domain, ontology, licensing and results.
+
+The pinned smoke input is the official repository example at commit
+`c17a118fcaed1559f03cc32cc3a91dedc557f8b8`:
+
+- point file: `utils/example/000104.bin`;
+- label file: `utils/example/000104.label`;
+- source points: `131,072`;
+- point SHA-256:
+  `ed81a9c3636d55b17d78058c72545d5d22419beecf174d50596d23ae178752af`;
+- label SHA-256:
+  `9b8c65b710873e931af4ac6dfc7d3dd2298696514ab721e50300bd55ad5b634e`;
+- official ontology config SHA-256:
+  `573379a232ac561805987466c391a61fd5ad338be7fb9c4c2842f3f28067e0ad`;
+- bounded browser preview: `20,000` deterministic even-index points;
+- coordinate frame: right-handed, `x` forward, `y` left, `z` up; no vehicle
+  transform, pose registration or deskew is claimed;
+- license: `CC-BY-NC-SA-3.0`; this is a research qualification source, not an
+  unrestricted commercial runtime dependency.
+
+Mission Core ground policy v1 treats `dirt`, `grass`, `asphalt`, `concrete` and
+`mud` as ground; clear structures, vegetation, people, vehicles and rubble as
+non-ground; and `void`, `water`, `sky`, generic `object` and `puddle` as
+`ignore`. The ignore set is excluded from future metrics instead of being
+silently counted as either free ground or obstacle. This mapping is a Mission
+Core evaluation decision, not an upstream RELLIS claim.
+
+The smoke closes reader, alignment, axes, palette and mapping compatibility
+only. The next gate admits the `14 GB` Ouster SemanticKITTI scans plus the
+`174 MB` labels and `174 MB` poses to D-only worker storage. Full ROS bags are
+not needed for the ground cross-check. Patchwork++ may be compared only after a
+physical Ouster mounting-height profile is evidenced; no height is inferred
+from the example cloud.
+
 ## First GOOSE admission evidence
 
 - worker root: canonical D-only root, path never exposed by the HTTP API;

docs/adr/0021-dataset-gateway-representation-boundary.md

@@ -39,6 +39,12 @@ first admitted source because it publishes off-road point-wise semantic and
 instance labels in SemanticKITTI-compatible `XYZI + uint32 label` files. Its
 annotated point-cloud file represents one LiDAR revolution.
 
+The gateway contract is multi-source, not GOOSE-shaped. RELLIS-3D v1.1 is the
+second source: it uses the same lossless SemanticKITTI ingress but keeps a
+separate Ouster OS1 domain, ontology, admission state, ground-target mapping,
+license and result set. Shared format never implies shared calibration,
+mounting height or commercial-use rights.
+
 The gateway:
 
 - preserves the native GOOSE frame before adaptation;
@@ -48,6 +54,10 @@ The gateway:
 - refuses automatic downloads of large archives;
 - admits storage only under `D:\NDC_MISSIONCORE\datasets` or its WSL mirror;
 - never promotes K1 `lio_pcl` to `native-scan`.
+- excludes explicitly ambiguous RELLIS classes through a versioned `ignore`
+  mask instead of silently scoring them as ground or obstacle;
+- exposes the RELLIS `CC-BY-NC-SA-3.0` restriction as research evidence and
+  never treats it as an unrestricted production dependency.
 
 Large-artifact execution remains worker-local. The browser receives only a
 path-free admission manifest and a bounded visualization preview. The canonical
@@ -82,6 +92,8 @@ unavailable rather than inventing timestamps.
 - Until bytes are installed, the UI exposes an explicit empty state. After a
   `frame-ready` worker admission, the same surface becomes an interactive
   source/remission/ground-truth viewer without changing the representation.
+- A bounded `smoke-ready` source may prove reader, axes, ontology and mapping
+  compatibility without claiming full-dataset or algorithm qualification.
 - Dataset and device inputs can share downstream algorithms only after their
   normalized contracts match.
 - Sensor adaptation may change range, FOV, point density, noise and dropout for
@@ -115,6 +127,7 @@ unavailable rather than inventing timestamps.
 - [GOOSE MuCAR-3 sensor setup](https://goose-dataset.de/docs/mucar3/)
 - [GOOSE paper and dimensioned sensor schematic](https://arxiv.org/pdf/2310.16788)
 - [Patchwork++ v1.4.1](https://github.com/url-kaist/patchwork-plusplus/tree/v1.4.1)
+- [RELLIS-3D official repository](https://github.com/unmannedlab/RELLIS-3D)
 - [Livox ROS Driver 2 point formats](https://github.com/Livox-SDK/livox_ros_driver2)
 - [Livox LIO motion-distortion handling](https://github.com/Livox-SDK/LIO-Livox)
 - [ROS FilterDeskew timestamp requirement](https://docs.ros.org/en/noetic/api/mp2p_icp/html/classmp2p__icp__filters_1_1FilterDeskew.html)

src/k1link/datasets/__init__.py

@@ -38,6 +38,15 @@ from k1link.datasets.goose_qualification import (
     GroundAcceptancePolicy,
     qualify_goose_ground,
 )
+from k1link.datasets.rellis_smoke import (
+    RELLIS_CLASSES,
+    RELLIS_GROUND_POLICY_SCHEMA,
+    RELLIS_PREVIEW_SCHEMA,
+    RELLIS_SOURCE_ID,
+    RellisSmokeError,
+    build_rellis_official_smoke_preview,
+    rellis_native_scan_preview,
+)
 
 __all__ = [
     "DATASET_GATEWAY_CATALOG_SCHEMA",
@@ -54,12 +63,18 @@ __all__ = [
     "GOOSE_QUALIFICATION_PREVIEW_SCHEMA",
     "GOOSE_QUALIFICATION_PROFILE_SCHEMA",
     "GOOSE_QUALIFICATION_REPORT_SCHEMA",
+    "RELLIS_CLASSES",
+    "RELLIS_GROUND_POLICY_SCHEMA",
+    "RELLIS_PREVIEW_SCHEMA",
+    "RELLIS_SOURCE_ID",
+    "RellisSmokeError",
     "GoosePatchworkProfile",
     "GroundAcceptancePolicy",
     "DegradationProfile",
     "DEFAULT_DEGRADATIONS",
     "benchmark_goose_current_ground",
     "benchmark_goose_patchwork_ground",
+    "build_rellis_official_smoke_preview",
     "configured_dataset_admission_manifest",
     "configured_dataset_ground_preview",
     "configured_dataset_preview",
@@ -69,5 +84,6 @@ __all__ = [
     "read_dataset_ground_preview",
     "read_dataset_native_scan_preview",
     "read_semantic_kitti_frame",
+    "rellis_native_scan_preview",
     "qualify_goose_ground",
 ]

src/k1link/datasets/cli.py

@@ -15,6 +15,10 @@ from k1link.datasets.goose_benchmark import (
 )
 from k1link.datasets.goose_qualification import qualify_goose_ground
 from k1link.datasets.goose_review import build_goose_ground_review_pack
+from k1link.datasets.rellis_smoke import (
+    RellisSmokeError,
+    build_rellis_official_smoke_preview,
+)
 
 app = typer.Typer(
     add_completion=False,
@@ -158,5 +162,50 @@ def build_goose_ground_review_command(
     typer.echo(json.dumps(manifest, ensure_ascii=False, sort_keys=True))
 
 
+@app.command("build-rellis-smoke-preview")
+def build_rellis_smoke_preview_command(
+    points: Annotated[
+        Path,
+        typer.Option("--points", exists=True, dir_okay=False, resolve_path=True),
+    ],
+    labels: Annotated[
+        Path,
+        typer.Option("--labels", exists=True, dir_okay=False, resolve_path=True),
+    ],
+    out: Annotated[
+        Path,
+        typer.Option("--out", dir_okay=False, resolve_path=True),
+    ],
+    preview_points: Annotated[
+        int,
+        typer.Option("--preview-points", min=1, max=50_000),
+    ] = 20_000,
+) -> None:
+    """Verify the pinned official RELLIS example and publish a bounded preview."""
+
+    try:
+        preview = build_rellis_official_smoke_preview(
+            points,
+            labels,
+            out,
+            preview_points=preview_points,
+        )
+    except RellisSmokeError as exc:
+        typer.echo(str(exc), err=True)
+        raise typer.Exit(code=2) from exc
+    typer.echo(
+        json.dumps(
+            {
+                "source_id": preview["source_id"],
+                "frame_id": preview["frame_id"],
+                "source_point_count": preview["source_point_count"],
+                "preview_point_count": preview["point_count"],
+            },
+            ensure_ascii=False,
+            sort_keys=True,
+        )
+    )
+
+
 if __name__ == "__main__":
     app()

src/k1link/datasets/gateway.py

@@ -18,7 +18,7 @@ import numpy.typing as npt
 
 from k1link.datasets.goose_profile import DEFAULT_GOOSE_PATCHWORK_PROFILE
 
-DATASET_GATEWAY_CATALOG_SCHEMA: Final = "missioncore.dataset-gateway-catalog/v2"
+DATASET_GATEWAY_CATALOG_SCHEMA: Final = "missioncore.dataset-gateway-catalog/v3"
 DATASET_ADMISSION_SCHEMA: Final = "missioncore.dataset-admission/v1"
 DATASET_PREVIEW_SCHEMA: Final = "missioncore.dataset-native-scan-preview/v1"
 DATASET_GROUND_PREVIEW_SCHEMA: Final = "missioncore.dataset-ground-comparison-preview/v2"
@@ -177,6 +177,7 @@ def _is_worker_d_storage(root: Path | None) -> bool:
 def dataset_gateway_catalog(
     dataset_root: Path | None = None,
     admission_manifest_path: Path | None = None,
+    rellis_preview_path: Path | None = None,
 ) -> dict[str, object]:
     """Return the path-free, read-only ingress plan and current admission state."""
 
@@ -196,6 +197,14 @@ def dataset_gateway_catalog(
     locally_admitted = _is_worker_d_storage(root)
     worker_admitted = bool(admission and admission["storage"]["admitted"])
     storage_admitted = locally_admitted or worker_admitted
+    rellis_preview: dict[str, Any] | None = None
+    if rellis_preview_path is not None and rellis_preview_path.is_file():
+        try:
+            candidate = read_dataset_native_scan_preview(rellis_preview_path)
+            if candidate.get("source_id") == "rellis-3d/v1.1":
+                rellis_preview = candidate
+        except DatasetAdmissionError:
+            pass
     source_status = (
         str(admission["status"])
         if admission is not None
@@ -212,6 +221,20 @@ def dataset_gateway_catalog(
         if storage_admitted
         else "configure-dataset-root-on-worker-d"
     )
+    rellis_status = (
+        "smoke-ready"
+        if rellis_preview is not None
+        else "ready-for-smoke"
+        if storage_admitted
+        else "blocked-storage-policy"
+    )
+    catalog_next_action = (
+        "admit-rellis-ouster-semantickitti-to-worker-d"
+        if rellis_preview is not None and source_status == "frame-ready"
+        else "build-rellis-official-example-smoke"
+        if source_status == "frame-ready"
+        else next_action
+    )
     return {
         "schema_version": DATASET_GATEWAY_CATALOG_SCHEMA,
         "access": "read-only",
@@ -234,11 +257,14 @@ def dataset_gateway_catalog(
         "sources": [
             {
                 "source_id": "goose-3d/v2025-08-22",
+                "source_kind": "goose",
                 "display_name": "GOOSE 3D",
                 "role": "primary-offroad-semantic-baseline",
                 "license": "CC-BY-SA-4.0",
+                "commercial_use": "allowed-with-share-alike",
                 "format": "semantickitti-xyzi-label",
                 "frame_semantics": "one-lidar-revolution",
+                "sensor": "VLS-128",
                 "platforms": ["MuCAR-3", "ALICE", "Spot"],
                 "annotations": ["semantic-point", "instance-point"],
                 "superclasses": [
@@ -255,10 +281,18 @@ def dataset_gateway_catalog(
                 "download": {
                     "automatic": False,
                     "reason": "operator-admitted-large-artifact-only",
+                    "smoke_example_mb": None,
+                    "primary_scan_archive_gb": 3.3,
+                    "label_archive_gb": None,
+                    "poses_archive_gb": None,
                     "training_archive_gb": 27.0,
                     "validation_archive_gb": 3.3,
                     "test_archive_gb": 3.3,
                 },
+                "statistics": {
+                    "fragment_count": 8,
+                    "annotated_scan_count": 961,
+                },
                 "admission": {
                     "status": source_status,
                     "native_scan": "ready-after-download",
@@ -267,7 +301,72 @@ def dataset_gateway_catalog(
                     "archive": admission["archive"] if admission is not None else None,
                     "frame": admission["frame"] if admission is not None else None,
                 },
-            }
+            },
+            {
+                "source_id": "rellis-3d/v1.1",
+                "source_kind": "rellis",
+                "display_name": "RELLIS-3D",
+                "role": "independent-offroad-cross-dataset-check",
+                "license": "CC-BY-NC-SA-3.0",
+                "commercial_use": "research-only-license-review-required",
+                "format": "semantickitti-xyzi-label",
+                "frame_semantics": "one-lidar-revolution",
+                "sensor": "Ouster OS1 64",
+                "platforms": ["Clearpath Warthog"],
+                "annotations": ["semantic-point"],
+                "superclasses": [
+                    "ground",
+                    "vegetation",
+                    "structure",
+                    "obstacle",
+                    "vehicle",
+                    "human",
+                    "water",
+                    "ignore",
+                ],
+                "download": {
+                    "automatic": False,
+                    "reason": "operator-admitted-large-artifact-only",
+                    "smoke_example_mb": 24.0,
+                    "primary_scan_archive_gb": 14.0,
+                    "label_archive_gb": 0.174,
+                    "poses_archive_gb": 0.174,
+                    "training_archive_gb": None,
+                    "validation_archive_gb": None,
+                    "test_archive_gb": None,
+                },
+                "statistics": {
+                    "fragment_count": 5,
+                    "annotated_scan_count": 13_556,
+                },
+                "admission": {
+                    "status": rellis_status,
+                    "native_scan": (
+                        "official-example-compatible"
+                        if rellis_preview is not None
+                        else "requires-official-example-smoke"
+                    ),
+                    "normalized_scan": "requires-explicit-frame-and-mounting-contract",
+                    "rolling_local_map": "requires-poses-timing-and-map-policy",
+                    "archive": None,
+                    "frame": (
+                        {
+                            "frame_id": rellis_preview["frame_id"],
+                            "point_count": rellis_preview["source_point_count"],
+                            "semantic_class_count": len(rellis_preview["classes"]),
+                            "ground_truth_ground_fraction": (
+                                sum(rellis_preview["ground_truth_ground"])
+                                / rellis_preview["point_count"]
+                            ),
+                            "preview_point_count": rellis_preview["point_count"],
+                            "preview_sha256": None,
+                            "preview_available": True,
+                        }
+                        if rellis_preview is not None
+                        else None
+                    ),
+                },
+            },
         ],
         "representations": [
             {
@@ -330,7 +429,7 @@ def dataset_gateway_catalog(
                 "reason": "post-lio-map-product-cannot-be-reconstructed-as-a-native-scan",
             }
         ],
-        "next_action": next_action,
+        "next_action": catalog_next_action,
     }
 
 
@@ -417,9 +516,13 @@ def read_dataset_admission_manifest(path: Path) -> dict[str, Any]:
 
 def read_dataset_native_scan_preview(path: Path) -> dict[str, Any]:
     document = _bounded_json_object(path, MAX_PREVIEW_BYTES, "dataset preview")
+    identity = (document.get("schema_version"), document.get("source_id"))
     if (
-        document.get("schema_version") != DATASET_PREVIEW_SCHEMA
-        or document.get("source_id") != "goose-3d/v2025-08-22"
+        identity
+        not in {
+            (DATASET_PREVIEW_SCHEMA, "goose-3d/v2025-08-22"),
+            ("missioncore.dataset-native-scan-preview/v2", "rellis-3d/v1.1"),
+        }
         or document.get("representation") != "native-scan"
         or document.get("sampling") != "deterministic-even-index"
     ):
@@ -433,6 +536,11 @@ def read_dataset_native_scan_preview(path: Path) -> dict[str, Any]:
     semantic_ids = document.get("semantic_label_ids")
     semantic_rgb = document.get("semantic_rgb_0_to_255")
     ground = document.get("ground_truth_ground")
+    evaluated = (
+        document.get("evaluation_mask")
+        if identity[1] == "rellis-3d/v1.1"
+        else [1] * point_count
+    )
     if (
         not isinstance(points, list)
         or len(points) != point_count
@@ -444,6 +552,8 @@ def read_dataset_native_scan_preview(path: Path) -> dict[str, Any]:
         or len(semantic_rgb) != point_count * 3
         or not isinstance(ground, list)
         or len(ground) != point_count
+        or not isinstance(evaluated, list)
+        or len(evaluated) != point_count
     ):
         raise DatasetAdmissionError("dataset preview arrays are not point-aligned")
     for point in points:
@@ -463,6 +573,7 @@ def read_dataset_native_scan_preview(path: Path) -> dict[str, Any]:
         (semantic_ids, 65_535, "semantic label"),
         (semantic_rgb, 255, "semantic color"),
         (ground, 1, "ground mask"),
+        (evaluated, 1, "evaluation mask"),
     ):
         if any(
             not isinstance(value, int) or isinstance(value, bool) or not 0 <= value <= maximum
@@ -473,16 +584,81 @@ def read_dataset_native_scan_preview(path: Path) -> dict[str, Any]:
     if not isinstance(classes, list) or len(classes) > 64:
         raise DatasetAdmissionError("dataset preview class catalog is incompatible")
     safety = _object(document.get("safety"), "safety")
-    if safety != {
+    expected_safety = {
         "visualization_only": True,
         "navigation_or_safety_accepted": False,
-    }:
+    }
+    if identity[1] == "rellis-3d/v1.1":
+        expected_safety["compatibility_smoke_only"] = True
+    if safety != expected_safety:
         raise DatasetAdmissionError("dataset preview safety boundary is incompatible")
     if not isinstance(document.get("frame_id"), str) or not document["frame_id"]:
         raise DatasetAdmissionError("dataset preview frame id is incompatible")
+    if identity[1] == "rellis-3d/v1.1":
+        _validate_rellis_preview_metadata(document, classes)
     return document
 
 
+def _validate_rellis_preview_metadata(
+    document: dict[str, Any],
+    classes: list[Any],
+) -> None:
+    coordinate_frame = _object(document.get("coordinate_frame"), "coordinate_frame")
+    if coordinate_frame != {
+        "frame_id": "sensor/lidar/os1",
+        "handedness": "right",
+        "x": "forward",
+        "y": "left",
+        "z": "up",
+        "transform_applied": False,
+    }:
+        raise DatasetAdmissionError("RELLIS coordinate frame is incompatible")
+    policy = _object(document.get("ground_policy"), "ground_policy")
+    if (
+        policy.get("schema_version") != "missioncore.rellis-ground-target-policy/v1"
+        or set(policy) != {"schema_version", "ground", "non_ground", "ignore"}
+        or any(
+            not isinstance(policy.get(key), list)
+            or any(not isinstance(value, str) or not value for value in policy[key])
+            for key in ("ground", "non_ground", "ignore")
+        )
+    ):
+        raise DatasetAdmissionError("RELLIS ground target policy is incompatible")
+    for item in classes:
+        value = _object(item, "class")
+        if (
+            value.get("ground_target") not in {"ground", "non-ground", "ignore"}
+            or not isinstance(value.get("label_id"), int)
+            or not isinstance(value.get("class_name"), str)
+            or not isinstance(value.get("hex"), str)
+            or not isinstance(value.get("source_point_count"), int)
+        ):
+            raise DatasetAdmissionError("RELLIS class catalog is incompatible")
+    evidence = _object(document.get("source_evidence"), "source_evidence")
+    if (
+        set(evidence)
+        != {
+            "repository_url",
+            "repository_commit",
+            "label_config_sha256",
+            "point_sha256",
+            "label_sha256",
+            "license",
+        }
+        or evidence.get("repository_url") != "https://github.com/unmannedlab/RELLIS-3D"
+        or evidence.get("repository_commit")
+        != "c17a118fcaed1559f03cc32cc3a91dedc557f8b8"
+        or evidence.get("label_config_sha256")
+        != "573379a232ac561805987466c391a61fd5ad338be7fb9c4c2842f3f28067e0ad"
+        or evidence.get("point_sha256")
+        != "ed81a9c3636d55b17d78058c72545d5d22419beecf174d50596d23ae178752af"
+        or evidence.get("label_sha256")
+        != "9b8c65b710873e931af4ac6dfc7d3dd2298696514ab721e50300bd55ad5b634e"
+        or evidence.get("license") != "CC-BY-NC-SA-3.0"
+    ):
+        raise DatasetAdmissionError("RELLIS source evidence is incompatible")
+
+
 def read_dataset_ground_preview(path: Path) -> dict[str, Any]:
     document = _bounded_json_object(path, MAX_PREVIEW_BYTES, "dataset ground preview")
     if (

src/k1link/datasets/rellis_smoke.py

@@ -0,0 +1,275 @@
+"""Pinned RELLIS-3D compatibility smoke for the shared Dataset Gateway.
+
+The smoke check deliberately stops before algorithm qualification.  It proves
+that Mission Core can read one official Ouster OS1 SemanticKITTI frame, preserve
+point/label alignment, apply an explicit ground-evaluation policy and publish a
+bounded visualization artifact.  Full RELLIS archives and ROS bags remain
+worker-D-only inputs.
+"""
+
+from __future__ import annotations
+
+import hashlib
+import json
+import os
+import tempfile
+from collections import Counter
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any, Final, Literal
+
+import numpy as np
+
+from k1link.datasets.gateway import DatasetFrameError, DatasetPointFrame, read_semantic_kitti_frame
+
+RELLIS_SOURCE_ID: Final = "rellis-3d/v1.1"
+RELLIS_PREVIEW_SCHEMA: Final = "missioncore.dataset-native-scan-preview/v2"
+RELLIS_GROUND_POLICY_SCHEMA: Final = "missioncore.rellis-ground-target-policy/v1"
+RELLIS_REPOSITORY_URL: Final = "https://github.com/unmannedlab/RELLIS-3D"
+RELLIS_REPOSITORY_COMMIT: Final = "c17a118fcaed1559f03cc32cc3a91dedc557f8b8"
+RELLIS_LABEL_CONFIG_SHA256: Final = (
+    "573379a232ac561805987466c391a61fd5ad338be7fb9c4c2842f3f28067e0ad"
+)
+RELLIS_EXAMPLE_POINTS_SHA256: Final = (
+    "ed81a9c3636d55b17d78058c72545d5d22419beecf174d50596d23ae178752af"
+)
+RELLIS_EXAMPLE_LABELS_SHA256: Final = (
+    "9b8c65b710873e931af4ac6dfc7d3dd2298696514ab721e50300bd55ad5b634e"
+)
+RELLIS_EXAMPLE_FRAME_ID: Final = "000104"
+RELLIS_LICENSE: Final = "CC-BY-NC-SA-3.0"
+MAX_RELLIS_PREVIEW_POINTS: Final = 50_000
+
+GroundTarget = Literal["ground", "non-ground", "ignore"]
+
+
+@dataclass(frozen=True)
+class RellisClass:
+    label_id: int
+    class_name: str
+    bgr: tuple[int, int, int]
+    ground_target: GroundTarget
+
+    @property
+    def rgb(self) -> tuple[int, int, int]:
+        blue, green, red = self.bgr
+        return red, green, blue
+
+    @property
+    def hex(self) -> str:
+        red, green, blue = self.rgb
+        return f"#{red:02x}{green:02x}{blue:02x}"
+
+    def to_preview_dict(self) -> dict[str, object]:
+        return {
+            "label_id": self.label_id,
+            "class_name": self.class_name,
+            "hex": self.hex,
+            "ground_target": self.ground_target,
+        }
+
+
+# IDs, names and BGR colors are pinned to the official repository config at
+# RELLIS_REPOSITORY_COMMIT.  The final column is Mission Core's versioned,
+# algorithm-scoped ground evaluation policy; it is not an upstream claim.
+RELLIS_CLASSES: Final[tuple[RellisClass, ...]] = (
+    RellisClass(0, "void", (0, 0, 0), "ignore"),
+    RellisClass(1, "dirt", (108, 64, 20), "ground"),
+    RellisClass(3, "grass", (0, 102, 0), "ground"),
+    RellisClass(4, "tree", (0, 255, 0), "non-ground"),
+    RellisClass(5, "pole", (0, 153, 153), "non-ground"),
+    RellisClass(6, "water", (0, 128, 255), "ignore"),
+    RellisClass(7, "sky", (0, 0, 255), "ignore"),
+    RellisClass(8, "vehicle", (255, 255, 0), "non-ground"),
+    RellisClass(9, "object", (255, 0, 127), "ignore"),
+    RellisClass(10, "asphalt", (64, 64, 64), "ground"),
+    RellisClass(12, "building", (255, 0, 0), "non-ground"),
+    RellisClass(15, "log", (102, 0, 0), "non-ground"),
+    RellisClass(17, "person", (204, 153, 255), "non-ground"),
+    RellisClass(18, "fence", (102, 0, 204), "non-ground"),
+    RellisClass(19, "bush", (255, 153, 204), "non-ground"),
+    RellisClass(23, "concrete", (170, 170, 170), "ground"),
+    RellisClass(27, "barrier", (41, 121, 255), "non-ground"),
+    RellisClass(31, "puddle", (134, 255, 239), "ignore"),
+    RellisClass(33, "mud", (99, 66, 34), "ground"),
+    RellisClass(34, "rubble", (110, 22, 138), "non-ground"),
+)
+RELLIS_CLASS_BY_ID: Final = {item.label_id: item for item in RELLIS_CLASSES}
+
+
+class RellisSmokeError(RuntimeError):
+    """The pinned official example cannot satisfy the RELLIS smoke contract."""
+
+
+def build_rellis_official_smoke_preview(
+    point_path: Path,
+    label_path: Path,
+    output_path: Path,
+    *,
+    preview_points: int = 20_000,
+) -> dict[str, Any]:
+    """Verify the official example and publish one bounded path-free preview."""
+
+    points_digest = _sha256_file(point_path)
+    labels_digest = _sha256_file(label_path)
+    if points_digest != RELLIS_EXAMPLE_POINTS_SHA256:
+        raise RellisSmokeError("RELLIS official example point digest is incompatible")
+    if labels_digest != RELLIS_EXAMPLE_LABELS_SHA256:
+        raise RellisSmokeError("RELLIS official example label digest is incompatible")
+    try:
+        frame = read_semantic_kitti_frame(point_path, label_path)
+    except DatasetFrameError as exc:
+        raise RellisSmokeError("RELLIS official example violates XYZI/label alignment") from exc
+    preview = rellis_native_scan_preview(
+        frame,
+        frame_id=RELLIS_EXAMPLE_FRAME_ID,
+        maximum_points=preview_points,
+        source_evidence={
+            "repository_url": RELLIS_REPOSITORY_URL,
+            "repository_commit": RELLIS_REPOSITORY_COMMIT,
+            "label_config_sha256": RELLIS_LABEL_CONFIG_SHA256,
+            "point_sha256": points_digest,
+            "label_sha256": labels_digest,
+            "license": RELLIS_LICENSE,
+        },
+    )
+    _atomic_json(output_path, preview)
+    return preview
+
+
+def rellis_native_scan_preview(
+    frame: DatasetPointFrame,
+    *,
+    frame_id: str,
+    maximum_points: int,
+    source_evidence: dict[str, str],
+) -> dict[str, Any]:
+    """Build the common viewer artifact from a validated RELLIS native frame."""
+
+    if not frame_id or not 1 <= maximum_points <= MAX_RELLIS_PREVIEW_POINTS:
+        raise RellisSmokeError("RELLIS preview bounds are incompatible")
+    unknown = sorted(
+        int(value)
+        for value in np.unique(frame.semantic_labels)
+        if int(value) not in RELLIS_CLASS_BY_ID
+    )
+    if unknown:
+        raise RellisSmokeError("RELLIS frame contains labels absent from the pinned ontology")
+    required_evidence = {
+        "repository_url",
+        "repository_commit",
+        "label_config_sha256",
+        "point_sha256",
+        "label_sha256",
+        "license",
+    }
+    if set(source_evidence) != required_evidence or any(
+        not isinstance(value, str) or not value for value in source_evidence.values()
+    ):
+        raise RellisSmokeError("RELLIS source evidence is incomplete")
+
+    sample_count = min(frame.point_count, maximum_points)
+    indices = np.linspace(0, frame.point_count - 1, sample_count, dtype=np.int64)
+    points = frame.points_xyz_m[indices]
+    remission = frame.remission[indices]
+    semantic = frame.semantic_labels[indices]
+    remission_min = float(np.min(remission))
+    remission_max = float(np.max(remission))
+    remission_span = remission_max - remission_min
+    if remission_span <= 0:
+        remission_u8 = np.zeros(sample_count, dtype=np.uint8)
+    else:
+        remission_u8 = np.rint(
+            (remission - remission_min) / remission_span * 255.0
+        ).astype(np.uint8)
+
+    ground = np.zeros(sample_count, dtype=np.uint8)
+    evaluated = np.zeros(sample_count, dtype=np.uint8)
+    colors = np.zeros((sample_count, 3), dtype=np.uint8)
+    for label_id in np.unique(semantic):
+        item = RELLIS_CLASS_BY_ID[int(label_id)]
+        mask = semantic == label_id
+        colors[mask] = item.rgb
+        if item.ground_target != "ignore":
+            evaluated[mask] = 1
+        if item.ground_target == "ground":
+            ground[mask] = 1
+
+    present = Counter(int(value) for value in frame.semantic_labels)
+    present_classes = [
+        {
+            **RELLIS_CLASS_BY_ID[label_id].to_preview_dict(),
+            "source_point_count": count,
+        }
+        for label_id, count in sorted(present.items())
+    ]
+    return {
+        "schema_version": RELLIS_PREVIEW_SCHEMA,
+        "source_id": RELLIS_SOURCE_ID,
+        "frame_id": frame_id,
+        "representation": "native-scan",
+        "sampling": "deterministic-even-index",
+        "source_point_count": frame.point_count,
+        "point_count": sample_count,
+        "points_xyz_m": points.tolist(),
+        "remission_0_to_255": remission_u8.tolist(),
+        "semantic_label_ids": semantic.astype(np.uint16).tolist(),
+        "semantic_rgb_0_to_255": colors.reshape(-1).tolist(),
+        "ground_truth_ground": ground.tolist(),
+        "evaluation_mask": evaluated.tolist(),
+        "classes": present_classes,
+        "coordinate_frame": {
+            "frame_id": "sensor/lidar/os1",
+            "handedness": "right",
+            "x": "forward",
+            "y": "left",
+            "z": "up",
+            "transform_applied": False,
+        },
+        "ground_policy": {
+            "schema_version": RELLIS_GROUND_POLICY_SCHEMA,
+            "ground": [
+                item.class_name for item in RELLIS_CLASSES if item.ground_target == "ground"
+            ],
+            "non_ground": [
+                item.class_name
+                for item in RELLIS_CLASSES
+                if item.ground_target == "non-ground"
+            ],
+            "ignore": [
+                item.class_name for item in RELLIS_CLASSES if item.ground_target == "ignore"
+            ],
+        },
+        "source_evidence": source_evidence,
+        "safety": {
+            "visualization_only": True,
+            "compatibility_smoke_only": True,
+            "navigation_or_safety_accepted": False,
+        },
+    }
+
+
+def _sha256_file(path: Path) -> str:
+    digest = hashlib.sha256()
+    try:
+        with path.open("rb") as source:
+            for chunk in iter(lambda: source.read(1024**2), b""):
+                digest.update(chunk)
+    except OSError as exc:
+        raise RellisSmokeError("RELLIS official example is unavailable") from exc
+    return digest.hexdigest()
+
+
+def _atomic_json(path: Path, document: dict[str, Any]) -> None:
+    path.parent.mkdir(parents=True, exist_ok=True)
+    with tempfile.NamedTemporaryFile(
+        mode="w",
+        dir=path.parent,
+        encoding="utf-8",
+        delete=False,
+    ) as temporary:
+        temporary_path = Path(temporary.name)
+        json.dump(document, temporary, ensure_ascii=False, separators=(",", ":"))
+        temporary.flush()
+        os.fsync(temporary.fileno())
+    os.replace(temporary_path, path)

src/k1link/web/app.py

@@ -426,6 +426,9 @@ app.include_router(
         dataset_preview_provider=lambda: (
             REPOSITORY_ROOT / ".runtime" / "dataset-gateway" / "preview.json"
         ),
+        dataset_rellis_preview_provider=lambda: (
+            REPOSITORY_ROOT / ".runtime" / "dataset-gateway" / "rellis-preview.json"
+        ),
         dataset_ground_preview_provider=lambda: (
             REPOSITORY_ROOT / ".runtime" / "dataset-gateway" / "ground-comparison.json"
         ),

src/k1link/web/lidar_api.py

@@ -4,7 +4,7 @@ import os
 import re
 from collections.abc import Callable
 from pathlib import Path
-from typing import Any, Final
+from typing import Annotated, Any, Final
 
 from fastapi import APIRouter, HTTPException, Query, Response
 
@@ -21,6 +21,7 @@ from k1link.compute import (
     lidar_pack_detail,
 )
 from k1link.datasets import (
+    RELLIS_SOURCE_ID,
     DatasetAdmissionError,
     configured_dataset_admission_manifest,
     configured_dataset_ground_preview,
@@ -62,6 +63,7 @@ def build_lidar_router(
     field_review_root_provider: RootProvider = configured_lidar_field_review_root,
     dataset_admission_provider: DatasetArtifactProvider = configured_dataset_admission_manifest,
     dataset_preview_provider: DatasetArtifactProvider = configured_dataset_preview,
+    dataset_rellis_preview_provider: DatasetArtifactProvider = lambda: None,
     dataset_ground_preview_provider: DatasetArtifactProvider = configured_dataset_ground_preview,
 ) -> APIRouter:
     router = APIRouter(prefix="/api/v1/lidar", tags=["lidar"])
@@ -70,18 +72,32 @@ def build_lidar_router(
     def get_dataset_gateway() -> dict[str, object]:
         return dataset_gateway_catalog(
             admission_manifest_path=dataset_admission_provider(),
+            rellis_preview_path=dataset_rellis_preview_provider(),
         )
 
     @router.get("/dataset-gateway/preview")
-    def get_dataset_gateway_preview() -> dict[str, Any]:
-        path = dataset_preview_provider()
+    def get_dataset_gateway_preview(
+        source_id: Annotated[
+            str,
+            Query(min_length=1, max_length=160),
+        ] = "goose-3d/v2025-08-22",
+    ) -> dict[str, Any]:
+        if source_id == "goose-3d/v2025-08-22":
+            path = dataset_preview_provider()
+        elif source_id == RELLIS_SOURCE_ID:
+            path = dataset_rellis_preview_provider()
+        else:
+            raise HTTPException(status_code=404, detail="Dataset source не найден.")
         if path is None or not path.is_file():
             raise HTTPException(
                 status_code=404,
-                detail="Первый размеченный native scan ещё не импортирован.",
+                detail="Размеченный native scan источника ещё не импортирован.",
             )
         try:
-            return read_dataset_native_scan_preview(path)
+            preview = read_dataset_native_scan_preview(path)
+            if preview["source_id"] != source_id:
+                raise DatasetAdmissionError("dataset preview source mismatch")
+            return preview
         except DatasetAdmissionError as exc:
             raise HTTPException(
                 status_code=500,

tests/test_dataset_gateway.py

@@ -12,6 +12,7 @@ from fastapi.routing import APIRoute
 from k1link.datasets import (
     DatasetAdmissionError,
     DatasetFrameError,
+    RELLIS_SOURCE_ID,
     dataset_gateway_catalog,
     goose_admission,
     goose_benchmark,
@@ -19,6 +20,7 @@ from k1link.datasets import (
     read_dataset_ground_preview,
     read_dataset_native_scan_preview,
     read_semantic_kitti_frame,
+    rellis_native_scan_preview,
 )
 from k1link.datasets.goose_admission import admit_goose_validation
 from k1link.datasets.goose_benchmark import (
@@ -111,10 +113,14 @@ def test_dataset_gateway_api_is_read_only_and_path_free(
     route = _endpoint(build_lidar_router(), "/api/v1/lidar/dataset-gateway")
     response = route()  # type: ignore[operator]
 
-    assert response["schema_version"] == "missioncore.dataset-gateway-catalog/v2"
+    assert response["schema_version"] == "missioncore.dataset-gateway-catalog/v3"
     assert response["access"] == "read-only"
     assert response["storage"]["admitted"] is True
     assert response["storage"]["path_exposed"] is False
+    assert [source["source_id"] for source in response["sources"]] == [
+        "goose-3d/v2025-08-22",
+        RELLIS_SOURCE_ID,
+    ]
     assert "/mnt/d/NDC_MISSIONCORE/datasets" not in repr(response).replace(
         response["storage"]["required_wsl_root"],  # type: ignore[index]
         "",
@@ -286,6 +292,70 @@ def test_dataset_preview_api_is_read_only_and_integrity_checked(
     assert response["frame_id"] == "frame-1"
 
 
+def test_rellis_smoke_preview_keeps_semantickitti_alignment_and_ignore_policy(
+    tmp_path: Path,
+) -> None:
+    points_path = tmp_path / "000104.bin"
+    labels_path = tmp_path / "000104.label"
+    np.asarray(
+        [
+            [1.0, 0.0, -1.0, 0.1],
+            [2.0, 0.2, -0.8, 0.2],
+            [3.0, -0.2, 0.5, 0.3],
+            [4.0, 0.0, -0.5, 0.4],
+        ],
+        dtype="<f4",
+    ).tofile(points_path)
+    np.asarray([3, 23, 4, 31], dtype="<u4").tofile(labels_path)
+    frame = read_semantic_kitti_frame(points_path, labels_path)
+
+    preview = rellis_native_scan_preview(
+        frame,
+        frame_id="000104",
+        maximum_points=4,
+        source_evidence={
+            "repository_url": "https://github.com/unmannedlab/RELLIS-3D",
+            "repository_commit": "c17a118fcaed1559f03cc32cc3a91dedc557f8b8",
+            "label_config_sha256": (
+                "573379a232ac561805987466c391a61fd5ad338be7fb9c4c2842f3f28067e0ad"
+            ),
+            "point_sha256": (
+                "ed81a9c3636d55b17d78058c72545d5d22419beecf174d50596d23ae178752af"
+            ),
+            "label_sha256": (
+                "9b8c65b710873e931af4ac6dfc7d3dd2298696514ab721e50300bd55ad5b634e"
+            ),
+            "license": "CC-BY-NC-SA-3.0",
+        },
+    )
+    preview_path = tmp_path / "rellis-preview.json"
+    preview_path.write_text(json.dumps(preview), encoding="utf-8")
+
+    decoded = read_dataset_native_scan_preview(preview_path)
+
+    assert decoded["source_id"] == RELLIS_SOURCE_ID
+    assert decoded["ground_truth_ground"] == [1, 1, 0, 0]
+    assert decoded["evaluation_mask"] == [1, 1, 1, 0]
+    assert decoded["coordinate_frame"]["x"] == "forward"
+    assert decoded["safety"]["compatibility_smoke_only"] is True
+
+    router = build_lidar_router(
+        dataset_admission_provider=lambda: None,
+        dataset_preview_provider=lambda: None,
+        dataset_rellis_preview_provider=lambda: preview_path,
+    )
+    route = _endpoint(router, "/api/v1/lidar/dataset-gateway/preview")
+    response = route(source_id=RELLIS_SOURCE_ID)  # type: ignore[operator]
+    assert response["frame_id"] == "000104"
+
+    catalog = dataset_gateway_catalog(
+        Path("/mnt/d/NDC_MISSIONCORE/datasets"),
+        rellis_preview_path=preview_path,
+    )
+    rellis = catalog["sources"][1]  # type: ignore[index]
+    assert rellis["admission"]["status"] == "smoke-ready"  # type: ignore[index]
+
+
 def test_goose_current_ground_is_scored_against_independent_labels(
     tmp_path: Path,
     monkeypatch: pytest.MonkeyPatch,