344 lines
10 KiB
Python
344 lines
10 KiB
Python
import numpy as np
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import pytest
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import open3d as o3d
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from scipy.spatial.transform import Rotation
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from aruco.icp_registration import (
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ICPConfig,
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ICPResult,
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ICPMetrics,
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extract_near_floor_band,
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compute_overlap_xz,
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compute_overlap_3d,
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apply_gravity_constraint,
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pairwise_icp,
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build_pose_graph,
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refine_with_icp,
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)
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from aruco.ground_plane import FloorPlane
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def test_extract_near_floor_band_basic():
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points = np.array(
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[[0, -0.1, 0], [0, 0.1, 0], [0, 0.2, 0], [0, 0.4, 0]], dtype=np.float64
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)
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floor_y = 0.0
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band_height = 0.3
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floor_normal = np.array([0, 1, 0], dtype=np.float64)
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result = extract_near_floor_band(points, floor_y, band_height, floor_normal)
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assert len(result) == 2
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assert np.all(result[:, 1] >= 0)
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assert np.all(result[:, 1] <= 0.3)
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def test_extract_near_floor_band_empty():
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points = np.zeros((0, 3))
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result = extract_near_floor_band(points, 0.0, 0.3, np.array([0, 1, 0]))
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assert len(result) == 0
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def test_extract_near_floor_band_all_in():
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points = np.random.uniform(0, 0.2, (100, 3))
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points[:, 1] = np.random.uniform(0.05, 0.25, 100)
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result = extract_near_floor_band(points, 0.0, 0.3, np.array([0, 1, 0]))
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assert len(result) == 100
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def test_compute_overlap_xz_full():
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points_a = np.array([[0, 0, 0], [1, 0, 1]])
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points_b = np.array([[0, 0, 0], [1, 0, 1]])
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area = compute_overlap_xz(points_a, points_b)
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assert abs(area - 1.0) < 1e-6
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def test_compute_overlap_xz_no():
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points_a = np.array([[0, 0, 0], [1, 0, 1]])
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points_b = np.array([[2, 0, 2], [3, 0, 3]])
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area = compute_overlap_xz(points_a, points_b)
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assert area == 0.0
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def test_compute_overlap_xz_partial():
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points_a = np.array([[0, 0, 0], [1, 0, 1]])
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points_b = np.array([[0.5, 0, 0.5], [1.5, 0, 1.5]])
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area = compute_overlap_xz(points_a, points_b)
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assert abs(area - 0.25) < 1e-6
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def test_compute_overlap_xz_with_margin():
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points_a = np.array([[0, 0, 0], [1, 0, 1]])
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points_b = np.array([[1.2, 0, 0], [2.2, 0, 1]])
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area_no_margin = compute_overlap_xz(points_a, points_b)
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area_with_margin = compute_overlap_xz(points_a, points_b, margin=0.5)
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assert area_no_margin == 0.0
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assert area_with_margin > 0.0
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def test_compute_overlap_3d_full():
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points_a = np.array([[0, 0, 0], [1, 1, 1]])
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points_b = np.array([[0, 0, 0], [1, 1, 1]])
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volume = compute_overlap_3d(points_a, points_b)
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assert abs(volume - 1.0) < 1e-6
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def test_compute_overlap_3d_no():
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points_a = np.array([[0, 0, 0], [1, 1, 1]])
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points_b = np.array([[2, 2, 2], [3, 3, 3]])
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volume = compute_overlap_3d(points_a, points_b)
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assert volume == 0.0
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def test_compute_overlap_3d_partial():
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# Overlap in [0.5, 1.0] for all axes -> 0.5^3 = 0.125
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points_a = np.array([[0, 0, 0], [1, 1, 1]])
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points_b = np.array([[0.5, 0.5, 0.5], [1.5, 1.5, 1.5]])
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volume = compute_overlap_3d(points_a, points_b)
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assert abs(volume - 0.125) < 1e-6
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def test_compute_overlap_3d_empty():
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points_a = np.zeros((0, 3))
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points_b = np.array([[0, 0, 0], [1, 1, 1]])
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assert compute_overlap_3d(points_a, points_b) == 0.0
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assert compute_overlap_3d(points_b, points_a) == 0.0
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def test_apply_gravity_constraint_identity():
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T = np.eye(4)
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result = apply_gravity_constraint(T, T)
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np.testing.assert_allclose(result, T, atol=1e-6)
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def test_apply_gravity_constraint_preserves_yaw():
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T_orig = np.eye(4)
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R_icp = Rotation.from_euler("xyz", [0, 10, 0], degrees=True).as_matrix()
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T_icp = np.eye(4)
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T_icp[:3, :3] = R_icp
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result = apply_gravity_constraint(T_icp, T_orig, penalty_weight=10.0)
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res_euler = Rotation.from_matrix(result[:3, :3]).as_euler("xyz", degrees=True)
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assert abs(res_euler[1] - 10.0) < 1e-6
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assert abs(res_euler[0]) < 1e-6
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assert abs(res_euler[2]) < 1e-6
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def test_apply_gravity_constraint_regularizes_pitch_roll():
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T_orig = np.eye(4)
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R_icp = Rotation.from_euler("xyz", [10, 0, 10], degrees=True).as_matrix()
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T_icp = np.eye(4)
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T_icp[:3, :3] = R_icp
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result = apply_gravity_constraint(T_icp, T_orig, penalty_weight=9.0)
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res_euler = Rotation.from_matrix(result[:3, :3]).as_euler("xyz", degrees=True)
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assert abs(res_euler[0] - 1.0) < 1e-2
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assert abs(res_euler[2] - 1.0) < 1e-2
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def create_box_pcd(size=1.0, num_points=500, seed=42):
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rng = np.random.default_rng(seed)
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points = rng.uniform(0, size, (num_points, 3))
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pcd = o3d.geometry.PointCloud()
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pcd.points = o3d.utility.Vector3dVector(points)
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return pcd
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def test_pairwise_icp_identity():
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pcd = create_box_pcd()
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config = ICPConfig(min_fitness=0.1)
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result = pairwise_icp(pcd, pcd, config, np.eye(4))
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assert result.converged
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assert result.fitness > 0.9
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np.testing.assert_allclose(result.transformation, np.eye(4), atol=1e-3)
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def test_pairwise_icp_known_transform():
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source = create_box_pcd()
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T_true = np.eye(4)
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T_true[:3, :3] = Rotation.from_euler("y", 5, degrees=True).as_matrix()
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T_true[:3, 3] = [0.05, 0, 0.02]
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target = o3d.geometry.PointCloud()
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target.points = o3d.utility.Vector3dVector(
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(np.asarray(source.points) @ T_true[:3, :3].T) + T_true[:3, 3]
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)
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config = ICPConfig(min_fitness=0.5, voxel_size=0.01)
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result = pairwise_icp(source, target, config, np.eye(4))
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assert result.converged
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np.testing.assert_allclose(result.transformation, T_true, atol=1e-2)
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def test_pairwise_icp_known_transform_gicp():
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source = create_box_pcd()
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T_true = np.eye(4)
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T_true[:3, :3] = Rotation.from_euler("y", 5, degrees=True).as_matrix()
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T_true[:3, 3] = [0.05, 0, 0.02]
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target = o3d.geometry.PointCloud()
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target.points = o3d.utility.Vector3dVector(
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(np.asarray(source.points) @ T_true[:3, :3].T) + T_true[:3, 3]
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)
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# GICP usually needs normals, which pairwise_icp estimates internally
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config = ICPConfig(min_fitness=0.5, voxel_size=0.01, method="gicp")
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result = pairwise_icp(source, target, config, np.eye(4))
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assert result.converged
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np.testing.assert_allclose(result.transformation, T_true, atol=1e-2)
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def test_pairwise_icp_insufficient_points():
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source = o3d.geometry.PointCloud()
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source.points = o3d.utility.Vector3dVector(np.random.rand(5, 3))
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target = o3d.geometry.PointCloud()
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target.points = o3d.utility.Vector3dVector(np.random.rand(5, 3))
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config = ICPConfig(min_fitness=0.9)
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result = pairwise_icp(source, target, config, np.eye(4))
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assert not result.converged
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def test_build_pose_graph_basic():
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serials = ["cam1", "cam2"]
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extrinsics = {"cam1": np.eye(4), "cam2": np.eye(4)}
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res = ICPResult(
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transformation=np.eye(4),
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fitness=1.0,
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inlier_rmse=0.0,
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information_matrix=np.eye(6),
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converged=True,
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)
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pair_results = {("cam1", "cam2"): res}
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graph = build_pose_graph(serials, extrinsics, pair_results, "cam1")
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assert len(graph.nodes) == 2
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assert len(graph.edges) == 1
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def test_build_pose_graph_disconnected():
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serials = ["cam1", "cam2", "cam3"]
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extrinsics = {"cam1": np.eye(4), "cam2": np.eye(4), "cam3": np.eye(4)}
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res = ICPResult(
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transformation=np.eye(4),
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fitness=1.0,
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inlier_rmse=0.0,
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information_matrix=np.eye(6),
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converged=True,
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)
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pair_results = {("cam1", "cam2"): res}
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graph = build_pose_graph(serials, extrinsics, pair_results, "cam1")
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assert len(graph.nodes) == 2
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assert len(graph.edges) == 1
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def test_refine_with_icp_synthetic_offset():
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import aruco.icp_registration
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import aruco.ground_plane
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box_points = create_box_pcd(size=0.5).points
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box_points = np.asarray(box_points)
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box_points[:, 1] -= 1.0
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box_points[:, 2] += 2.0
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def mock_unproject(depth, K, stride=1, **kwargs):
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if depth[0, 0] == 1.0:
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return box_points
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else:
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return box_points - np.array([1.0, 0, 0])
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orig_unproject = aruco.ground_plane.unproject_depth_to_points
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aruco.ground_plane.unproject_depth_to_points = mock_unproject
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try:
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camera_data = {
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"cam1": {"depth": np.ones((10, 10)), "K": np.eye(3)},
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"cam2": {"depth": np.zeros((10, 10)), "K": np.eye(3)},
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}
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T_w1 = np.eye(4)
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T_w2_est = np.eye(4)
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T_w2_est[0, 3] = 1.05
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extrinsics = {"cam1": T_w1, "cam2": T_w2_est}
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floor_planes = {
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"cam1": FloorPlane(normal=np.array([0, 1, 0]), d=1.0),
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"cam2": FloorPlane(normal=np.array([0, 1, 0]), d=1.0),
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}
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config = ICPConfig(
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min_overlap_area=0.01,
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min_fitness=0.1,
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voxel_size=0.05,
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max_iterations=[20, 10, 5],
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max_translation_m=3.0,
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)
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new_extrinsics, metrics = refine_with_icp(
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camera_data, extrinsics, floor_planes, config
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)
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assert metrics.success
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assert metrics.num_cameras_optimized == 2
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assert abs(new_extrinsics["cam2"][0, 3] - T_w2_est[0, 3]) > 0.01
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finally:
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aruco.ground_plane.unproject_depth_to_points = orig_unproject
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def test_refine_with_icp_no_overlap():
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import aruco.icp_registration
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import aruco.ground_plane
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def mock_unproject(depth, K, stride=1, **kwargs):
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if depth[0, 0] == 1.0:
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return np.random.rand(200, 3) + [0, -1, 0]
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else:
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return np.random.rand(200, 3) + [10, -1, 0]
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orig_unproject = aruco.ground_plane.unproject_depth_to_points
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aruco.ground_plane.unproject_depth_to_points = mock_unproject
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try:
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camera_data = {
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"cam1": {"depth": np.ones((10, 10)), "K": np.eye(3)},
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"cam2": {"depth": np.zeros((10, 10)), "K": np.eye(3)},
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}
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extrinsics = {"cam1": np.eye(4), "cam2": np.eye(4)}
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floor_planes = {
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"cam1": FloorPlane(normal=np.array([0, 1, 0]), d=1.0),
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"cam2": FloorPlane(normal=np.array([0, 1, 0]), d=1.0),
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}
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config = ICPConfig(min_overlap_area=1.0)
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new_extrinsics, metrics = refine_with_icp(
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camera_data, extrinsics, floor_planes, config
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)
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assert metrics.num_cameras_optimized == 1
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assert metrics.success
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finally:
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aruco.ground_plane.unproject_depth_to_points = orig_unproject
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def test_refine_with_icp_single_camera():
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camera_data = {"cam1": {"depth": np.ones((10, 10)), "K": np.eye(3)}}
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extrinsics = {"cam1": np.eye(4)}
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floor_planes = {"cam1": FloorPlane(normal=np.array([0, 1, 0]), d=1.0)}
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config = ICPConfig()
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new_extrinsics, metrics = refine_with_icp(
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camera_data, extrinsics, floor_planes, config
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)
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assert metrics.num_cameras_optimized == 1
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assert metrics.success
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