Remove flaky test_06 marker injection test

The marker injection test was unreliable because it published
pointclouds without maintaining TF updates, causing the node to
drop messages due to stale transforms.

The axis-swap regression is already thoroughly covered by:
- 11 unit tests in test_map_shifting.py
- Integration tests 01-05 for TF → GridMap pipeline

Author: Idate96

elevation_mapping_cupy/test/test_tf_gridmap_integration.py

@@ -583,154 +583,6 @@ def test_05_no_axis_swap(self):
         self.assertLess(x_change_from_y_move, 0.15,
                         msg=f"X changed by {x_change_from_y_move} when only Y moved - AXIS SWAP BUG!")
 
-    def test_06_marker_data_shifts_with_robot_movement(self):
-        """
-        Test that actual elevation data shifts correctly when robot moves.
-
-        This test:
-        1. Places robot at origin
-        2. Injects a marker pointcloud at world position (1.0, 0.0, 0.5)
-        3. Verifies elevation data appears in the grid
-        4. Moves robot +0.5m in X
-        5. Verifies the marker data shifted correctly in the grid
-
-        This tests the actual cp.roll shifting, not just the pose tracking.
-        """
-        self._require_dds()
-
-        resolution = 0.1  # From test config
-
-        # Position robot at origin
-        for _ in range(30):
-            self.fixture.publish_tf(0.0, 0.0, 0.0)
-            self.spin_for(0.1)
-
-        self._prime_map_with_pointcloud(repeats=5)
-
-        self.wait_for_gridmap_with_spin(timeout=10.0)
-        center_before_marker = self.fixture.get_gridmap_center()
-        self.assertIsNotNone(center_before_marker, "No GridMap received before marker injection")
-
-        # Inject marker pointcloud at (1.0, 0.0, 0.5) in world frame
-        # This is 1m ahead of robot in X direction
-        marker_x = center_before_marker[0] + 1.0
-        marker_y = center_before_marker[1]
-        marker_z = 0.5
-        for _ in range(30):
-            self.fixture.publish_marker_pointcloud(marker_x, marker_y, marker_z)
-            self.spin_for(0.2)
-
-        # Wait for map to be updated
-        self.wait_for_gridmap_with_spin(timeout=10.0)
-
-        # Get elevation data and find the marker
-        gridmap = self.fixture.last_gridmap
-        self.assertIsNotNone(gridmap, "No GridMap received")
-
-        elevation_data = self._extract_elevation_layer(gridmap)
-        self.assertIsNotNone(elevation_data, "Could not extract elevation layer")
-        self.fixture.get_logger().info(
-            f"Elevation stats before move: min={np.nanmin(elevation_data):.4f}, "
-            f"max={np.nanmax(elevation_data):.4f}, nan_fraction={np.isnan(elevation_data).mean():.3f}"
-        )
-
-        # Find cells with non-zero elevation (the marker)
-        initial_marker_cells = self._find_nonzero_cells(elevation_data, threshold=0.01)
-        if len(initial_marker_cells) == 0:
-            self.skipTest(
-                "Marker not registered in map - pointcloud may not be reaching node in this environment."
-            )
-
-        # Record initial marker position in grid
-        initial_marker_center = np.mean(initial_marker_cells, axis=0)
-        self.fixture.get_logger().info(f"Initial marker at grid cells: {initial_marker_cells}")
-
-        # Move robot +0.5m in X direction (relative to current center)
-        target_x = center_before_marker[0] + 0.5
-        target_y = center_before_marker[1]
-        for _ in range(30):
-            self.fixture.publish_tf(target_x, target_y, 0.0)
-            self.spin_for(0.1)
-
-        self._prime_map_with_pointcloud(repeats=5, tf_x=target_x, tf_y=target_y)
-
-        # Wait for map to update
-        self.wait_for_gridmap_with_spin(timeout=10.0)
-
-        # Get new elevation data
-        gridmap = self.fixture.last_gridmap
-        new_elevation_data = self._extract_elevation_layer(gridmap)
-        self.assertIsNotNone(new_elevation_data,
-            "Could not extract elevation layer after movement")
-        self.fixture.get_logger().info(
-            f"Elevation stats after move: min={np.nanmin(new_elevation_data):.4f}, "
-            f"max={np.nanmax(new_elevation_data):.4f}, nan_fraction={np.isnan(new_elevation_data).mean():.3f}"
-        )
-
-        # Find marker in new position
-        new_marker_cells = self._find_nonzero_cells(new_elevation_data, threshold=0.01)
-        self.assertGreater(len(new_marker_cells), 0,
-                          "Marker data lost after robot movement")
-
-        new_marker_center = np.mean(new_marker_cells, axis=0)
-        self.fixture.get_logger().info(f"New marker at grid cells: {new_marker_cells}")
-
-        # The marker should have shifted in the grid
-        # Robot moved +0.5m in X, so the marker (at fixed world position) should
-        # appear to shift BACKWARD relative to the robot-centered grid.
-        #
-        # In grid coordinates (row=Y, col=X):
-        # - X movement → column shift (shift[1] in row-major indexing)
-        # - Y movement → row shift (shift[0] in row-major indexing)
-        #
-        # With the axis-swap bug, X robot movement would incorrectly cause row shift.
-        shift = new_marker_center - initial_marker_center
-        self.fixture.get_logger().info(f"Grid shift: {shift} (row, col)")
-
-        expected_shift_cells = int(0.5 / resolution)  # 5 cells
-
-        # CRITICAL: Check DIRECTION, not just magnitude
-        # Robot moved +X, so marker should shift in column direction (shift[1]),
-        # NOT in row direction (shift[0])
-        col_shift = abs(shift[1])  # Should be ~5 cells
-        row_shift = abs(shift[0])  # Should be ~0 cells
-
-        self.assertGreater(col_shift, expected_shift_cells * 0.5,
-                          f"Marker should shift ~{expected_shift_cells} cells in column (X) direction, "
-                          f"got col_shift={col_shift}")
-        self.assertLess(row_shift, expected_shift_cells * 0.3,
-                       f"Marker should NOT shift in row (Y) direction for X-only robot movement, "
-                       f"got row_shift={row_shift} - AXIS SWAP BUG!")
-
-    def _extract_elevation_layer(self, gridmap: GridMap) -> np.ndarray:
-        """Extract the elevation layer from a GridMap message."""
-        try:
-            if 'elevation' not in gridmap.layers:
-                return None
-            idx = gridmap.layers.index('elevation')
-            data_msg = gridmap.data[idx]
-
-            # Extract dimensions from layout
-            if len(data_msg.layout.dim) >= 2:
-                cols = data_msg.layout.dim[0].size
-                rows = data_msg.layout.dim[1].size
-            else:
-                # Assume square
-                size = int(np.sqrt(len(data_msg.data)))
-                rows, cols = size, size
-
-            data = np.array(data_msg.data, dtype=np.float32).reshape(rows, cols)
-            return data
-        except Exception as e:
-            self.fixture.get_logger().warning(f"Failed to extract elevation: {e}")
-            return None
-
-    def _find_nonzero_cells(self, data: np.ndarray, threshold: float = 0.1) -> np.ndarray:
-        """Find grid cells with values above threshold (non-empty cells)."""
-        # Filter out NaN and find cells with elevation
-        valid_mask = ~np.isnan(data) & (np.abs(data) > threshold)
-        indices = np.argwhere(valid_mask)
-        return indices
 
 
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