feat(lab): separate current increment from rolling map

apps/control-station/src/components/laboratory/LaboratoryMetricEvidenceScene.tsx

@@ -10,7 +10,7 @@ export type LaboratoryMetricSceneMode = "3d" | "plan";
 export interface LaboratoryMetricObstacleVisual {
   id: string;
   decision: LaboratoryMetricDecision;
-  state: "current" | "held" | "expired";
+  state: "current" | "retained" | "held" | "expired";
   centroidBodyXyzM: LaboratoryMetricPoint3;
   cellCentersBodyXyzM: readonly LaboratoryMetricPoint3[];
 }
@@ -103,6 +103,8 @@ export function LaboratoryMetricEvidenceScene({
   const controlsRef = useRef<OrbitControls | null>(null);
   const contentRef = useRef<THREE.Group | null>(null);
   const [renderError, setRenderError] = useState<string | null>(null);
+  const [showCurrentIncrement, setShowCurrentIncrement] = useState(true);
+  const [showRollingMap, setShowRollingMap] = useState(true);
 
   useEffect(() => {
     const host = hostRef.current;
@@ -185,24 +187,34 @@ export function LaboratoryMetricEvidenceScene({
       child.traverse(disposeRenderable);
     }
 
-    const contextGeometry = new THREE.BufferGeometry();
-    contextGeometry.setAttribute(
-      "position",
-      new THREE.BufferAttribute(positions(pointCloudBodyXyzM), 3),
-    );
-    content.add(new THREE.Points(
-      contextGeometry,
-      new THREE.PointsMaterial({
-        color: tokenColor(host, "--nodedc-text-muted", [147, 151, 159]),
-        size: 1.7,
-        sizeAttenuation: false,
-        transparent: true,
-        opacity: 0.34,
-        depthWrite: false,
-      }),
-    ));
+    if (showCurrentIncrement) {
+      const contextGeometry = new THREE.BufferGeometry();
+      contextGeometry.setAttribute(
+        "position",
+        new THREE.BufferAttribute(positions(pointCloudBodyXyzM), 3),
+      );
+      content.add(new THREE.Points(
+        contextGeometry,
+        new THREE.PointsMaterial({
+          color: tokenColor(host, "--nodedc-text-muted", [147, 151, 159]),
+          size: 1.7,
+          sizeAttenuation: false,
+          transparent: true,
+          opacity: 0.34,
+          depthWrite: false,
+        }),
+      ));
+    }
 
     for (const obstacle of obstacles) {
+      if (
+        (obstacle.state === "current" && !showCurrentIncrement)
+        || (obstacle.state === "retained" && !showRollingMap)
+        || obstacle.state === "held"
+        || obstacle.state === "expired"
+      ) {
+        continue;
+      }
       const color = decisionColor(host, obstacle.decision);
       const cellsGeometry = new THREE.BufferGeometry();
       cellsGeometry.setAttribute(
@@ -213,16 +225,19 @@ export function LaboratoryMetricEvidenceScene({
         cellsGeometry,
         new THREE.PointsMaterial({
           color,
-          size: obstacle.state === "current" ? 4.8 : 3.8,
+          size: obstacle.state === "current" ? 4.8 : 5.2,
           sizeAttenuation: false,
           transparent: true,
-          opacity: obstacle.state === "current" ? 0.94 : 0.45,
+          opacity: obstacle.state === "current" ? 0.94 : 0.78,
           depthWrite: false,
         }),
       ));
       const centroid = new THREE.Mesh(
         new THREE.SphereGeometry(0.1, 16, 12),
-        new THREE.MeshBasicMaterial({ color, wireframe: obstacle.state !== "current" }),
+        new THREE.MeshBasicMaterial({
+          color,
+          wireframe: obstacle.state === "retained",
+        }),
       );
       centroid.position.fromArray(scenePoint(obstacle.centroidBodyXyzM));
       centroid.userData.evidenceId = obstacle.id;
@@ -287,7 +302,14 @@ export function LaboratoryMetricEvidenceScene({
       material.depthWrite = false;
     });
     content.add(grid);
-  }, [corridor, obstacles, pointCloudBodyXyzM, rig]);
+  }, [
+    corridor,
+    obstacles,
+    pointCloudBodyXyzM,
+    rig,
+    showCurrentIncrement,
+    showRollingMap,
+  ]);
 
   const resetView = () => {
     const camera = cameraRef.current;
@@ -321,13 +343,30 @@ export function LaboratoryMetricEvidenceScene({
         >
           Сбросить ракурс
         </Button>
+        <Button
+          variant={showCurrentIncrement ? "primary" : "secondary"}
+          size="compact"
+          aria-pressed={showCurrentIncrement}
+          onClick={() => setShowCurrentIncrement((visible) => !visible)}
+        >
+          CURRENT INCREMENT
+        </Button>
+        <Button
+          variant={showRollingMap ? "primary" : "secondary"}
+          size="compact"
+          aria-pressed={showRollingMap}
+          onClick={() => setShowRollingMap((visible) => !visible)}
+        >
+          ROLLING MAP
+        </Button>
         <span>ЛКМ · вращение · колесо · масштаб · ПКМ · панорама</span>
       </div>
       <div className="laboratory-metric-evidence-scene__legend">
         <span data-decision="threat">Угроза</span>
         <span data-decision="not-threat">Вне коридора</span>
         <span data-decision="unknown">Неизвестно</span>
-        <span data-decision="context">LiDAR context</span>
+        <span data-decision="context">Current increment</span>
+        <span data-decision="rolling">Rolling-map occupied</span>
       </div>
     </div>
   );

apps/control-station/src/core/laboratory/m4ReplayThreat.ts

@@ -18,6 +18,7 @@ export interface M4ThreatReplayResult {
     evidence: {
       cameraOnly: number;
       currentMetric: number;
+      rollingMapRetained: number;
       staleOrHeld: number;
     };
     fixtures: {
@@ -69,7 +70,7 @@ export interface M4ThreatAssessment {
 
 export interface M4ThreatMetricVisual {
   componentId: string;
-  state: "current" | "held" | "expired";
+  state: "current" | "retained" | "held" | "expired";
   motion: M4ThreatMotion;
   centroidBodyXyzM: M4Point3;
   cellCentersBodyXyzM: readonly M4Point3[];
@@ -96,6 +97,8 @@ export interface M4ThreatVisualFrame {
   pointCloudBodyXyzM: readonly M4Point3[];
   pointCloudSourceCount: number;
   pointCloudSampleCount: number;
+  pointCloudLayer: "current-increment";
+  rollingMapComponentCount: number;
   metricObstacles: readonly M4ThreatMetricVisual[];
   cameraProposals: readonly M4ThreatCameraProposal[];
   rig: {
@@ -296,6 +299,9 @@ export async function fetchM4ThreatReplayResult({
       evidence: {
         cameraOnly: integer(evidence["camera-only"], "M4.6 camera-only"),
         currentMetric: integer(evidence["current-metric"], "M4.6 metric"),
+        rollingMapRetained: evidence["rolling-map-retained"] === undefined
+          ? 0
+          : integer(evidence["rolling-map-retained"], "M4.6 rolling map"),
         staleOrHeld: integer(evidence["stale-or-held"], "M4.6 stale"),
       },
       fixtures: {
@@ -389,7 +395,14 @@ export async function fetchM4ThreatVisual(
   );
   if (!response.ok) throw new M4ThreatContractError(`M4.6 visual frame: HTTP ${response.status}.`);
   const item = object(await response.json(), "M4.6 visual frame");
-  exact(item.schema_version, "missioncore.perception-threat-visual-frame/v1", "M4.6 frame schema");
+  const frameSchema = text(item.schema_version, "M4.6 frame schema");
+  if (
+    frameSchema !== "missioncore.perception-threat-visual-frame/v1"
+    && frameSchema !== "missioncore.perception-threat-visual-frame/v2"
+  ) {
+    throw new M4ThreatContractError("M4.6 frame schema: нарушен контракт.");
+  }
+  const rollingMapV2 = frameSchema === "missioncore.perception-threat-visual-frame/v2";
   exact(item.result_id, result, "M4.6 frame result");
   const rig = object(item.rig, "M4.6 visual rig");
   const corridor = object(item.corridor, "M4.6 visual corridor");
@@ -404,10 +417,21 @@ export async function fetchM4ThreatVisual(
     ),
     pointCloudSourceCount: integer(item.point_cloud_source_count, "M4.6 source points"),
     pointCloudSampleCount: integer(item.point_cloud_sample_count, "M4.6 sample points"),
+    pointCloudLayer: rollingMapV2
+      ? exact(item.point_cloud_layer, "current-increment", "M4.6 point layer")
+      : "current-increment",
+    rollingMapComponentCount: rollingMapV2
+      ? integer(item.rolling_map_component_count, "M4.6 rolling components")
+      : 0,
     metricObstacles: array(item.metric_obstacles, "M4.6 metric visuals").map((raw) => {
       const value = object(raw, "M4.6 metric visual");
       const state = text(value.state, "M4.6 temporal state");
-      if (state !== "current" && state !== "held" && state !== "expired") {
+      if (
+        state !== "current"
+        && state !== "retained"
+        && state !== "held"
+        && state !== "expired"
+      ) {
         throw new M4ThreatContractError("M4.6 temporal state: неизвестное состояние.");
       }
       return {

apps/control-station/src/styles/m4-replay-threat.css

@@ -103,6 +103,12 @@
   background: rgb(var(--nodedc-warning-rgb));
 }
 
+.laboratory-metric-evidence-scene__legend span[data-decision="rolling"]::before {
+  box-sizing: border-box;
+  border: 1px solid rgb(var(--nodedc-accent-rgb));
+  background: transparent;
+}
+
 @media (max-width: 900px) {
   .laboratory-metric-evidence-scene__toolbar > span {
     display: none;

apps/control-station/src/workspaces/laboratory/M4ReplayThreatResult.tsx

@@ -52,14 +52,14 @@ export function M4ReplayThreatResultView({
           ]}
           brief={{
             question: "Может ли единый слой обнаруживать потенциальное препятствие по двум независимым источникам, не теряя LiDAR-only объекты и не объявляя camera-only наблюдение безопасным?",
-            approach: "Все 4489 кадров RAVNOVES00 повторно пропущены через неизменяемые detector, metric geometry и temporal ledgers. Виртуальный base_footprint привязан к gravity-оси SLAM map и направлению сглаженной траектории, проверенному camera extrinsic. Geometry-only объекты получают метрическую оценку; camera-only и stale/held остаются unknown.",
-            principalResult: `${metrics.evidence.currentMetric.toLocaleString("ru-RU")} current metric и ${metrics.evidence.cameraOnly.toLocaleString("ru-RU")} camera-only наблюдений учтены; ${metrics.reasonCounts["geometry-only-evidence"]?.toLocaleString("ru-RU") ?? "0"} geometry-only оценок не потеряны. Критические fixtures: ${metrics.fixtures.passed}/${metrics.fixtures.total}, ложных safe: ${metrics.fixtures.criticalFalseNotThreat}.`,
+            approach: "Все 4489 кадров RAVNOVES00 повторно пропущены через неизменяемые detector, metric geometry и temporal ledgers. Текущий lio_pcl increment хранится отдельно от bounded rolling map: отсутствие повторной публикации точки не считается свободным пространством. Виртуальный base_footprint привязан к gravity-оси SLAM map и направлению сглаженной траектории, проверенному camera extrinsic.",
+            principalResult: `${metrics.evidence.currentMetric.toLocaleString("ru-RU")} current metric, ${metrics.evidence.rollingMapRetained.toLocaleString("ru-RU")} rolling-map и ${metrics.evidence.cameraOnly.toLocaleString("ru-RU")} camera-only публикаций учтены. Кадр 1880 удерживает обе видимые бетонные полусферы; критические fixtures: ${metrics.fixtures.passed}/${metrics.fixtures.total}, ложных safe: ${metrics.fixtures.criticalFalseNotThreat}.`,
             limitation: "Корпус и коридор пока виртуальные, replay не является live-проходом или физическим collision test. На машине виртуальная привязка должна замениться измеренным rigid T_body_from_sensor; independent object truth остаётся следующим gate.",
           }}
           method={{
             completeness: "complete",
             executionClass: "hybrid",
-            pipelineId: "dual-evidence-replay-threat/v2",
+            pipelineId: "dual-evidence-replay-threat/v3",
             components: [
               {
                 kind: "source",
@@ -78,8 +78,8 @@ export function M4ReplayThreatResultView({
               {
                 kind: "source",
                 name: result.sourceResultIds.temporal,
-                version: "frozen temporal object map",
-                role: "current / held / expired и bounded motion history",
+                version: "frozen temporal + rolling obstacle map",
+                role: "current increment / rolling retained / bounded motion history",
                 identitySha256: result.sourceResultIds.temporal.split("-").at(-1) ?? null,
               },
               {
@@ -117,7 +117,7 @@ export function M4ReplayThreatResultView({
             {
               label: "Metric evidence",
               value: metrics.evidence.currentMetric.toLocaleString("ru-RU"),
-              hint: `${metrics.reasonCounts["geometry-only-evidence"]?.toLocaleString("ru-RU") ?? "0"} geometry-only`,
+              hint: `${metrics.evidence.rollingMapRetained.toLocaleString("ru-RU")} rolling-map publications`,
             },
             {
               label: "Threat / clear",
@@ -131,7 +131,7 @@ export function M4ReplayThreatResultView({
             },
           ]}
           conclusion={{
-            proved: `На неизменяемом RAVNOVES00 каждый metric, stale/held и camera-only объект получил ровно одну консервативную оценку. ${metrics.bodyFrame.qualified}/${metrics.bodyFrame.available} доступных body frames квалифицированы без переноса handheld roll/pitch на SLAM-мир; camera/route alignment p95 ${formatNumber(metrics.bodyFrame.cameraForwardAlignmentDeg.p95, 1)}°. Видео и точное 3D-доказательство доступны в одном viewer.`,
+            proved: `На неизменяемом RAVNOVES00 каждый current, rolling-map, stale/held и camera-only объект получил ровно одну консервативную оценку. CURRENT INCREMENT и ROLLING MAP независимо включаются в viewer; кадр 1880 закреплён как регрессия двух бетонных полусфер. ${metrics.bodyFrame.qualified}/${metrics.bodyFrame.available} body frames квалифицированы без переноса handheld roll/pitch на SLAM-мир.`,
             notProved: "Не доказаны live realtime, измеренный T_body_from_sensor и геометрия физического корпуса, независимая object-level правильность, навигационная или safety-пригодность и выдача команд.",
             decision: "Сохранить dual-evidence provider как канонический replay seam и переходить к независимому object-centric gate; физическую геометрию и live/actuation authority не смешивать с дальнейшей CV-разработкой.",
           }}

apps/control-station/src/workspaces/laboratory/M4ReplayThreatVisual.tsx

@@ -179,6 +179,12 @@ export function M4ReplayThreatVisual({ resultId }: { resultId: string }) {
   const threatObstacles = frame?.metricObstacles.filter(
     (item) => item.assessment.decision === "threat",
   ) ?? [];
+  const currentIncrementObstacles = frame?.metricObstacles.filter(
+    (item) => item.state === "current",
+  ) ?? [];
+  const rollingMapObstacles = frame?.metricObstacles.filter(
+    (item) => item.state === "retained",
+  ) ?? [];
   const nearest = frame?.metricObstacles
     .map((item) => item.assessment.closestApproachM)
     .filter((value): value is number => value !== null)
@@ -293,9 +299,14 @@ export function M4ReplayThreatVisual({ resultId }: { resultId: string }) {
         <small>{(frame.sourceTimeNs / 1_000_000_000).toFixed(3)} с · {selectedItem?.frameId}</small>
       </div>
       <div>
-        <span>Dual evidence</span>
-        <strong>{frame.metricObstacles.length} metric · {frame.cameraProposals.length} camera</strong>
-        <small>{frame.pointCloudSampleCount}/{frame.pointCloudSourceCount} LiDAR points shown</small>
+        <span>Representation layers</span>
+        <strong>
+          {currentIncrementObstacles.length} current · {rollingMapObstacles.length} rolling
+        </strong>
+        <small>
+          CURRENT INCREMENT {frame.pointCloudSampleCount}/{frame.pointCloudSourceCount} points
+          · ROLLING MAP {frame.rollingMapComponentCount} components
+        </small>
       </div>
       <div>
         <span>Virtual corridor</span>
@@ -356,7 +367,7 @@ export function M4ReplayThreatVisual({ resultId }: { resultId: string }) {
         rig={frame.rig}
         corridor={frame.corridor}
         mode={mode}
-        label={`M4.6 metric point cloud, frame ${frame.sequence}`}
+        label={`M4.6 current increment and rolling map, frame ${frame.sequence}`}
       />
     );
   }