#!/usr/bin/env python3 """Interactive 3D comparison of raw, RTK, GICP and hand-eye-predicted motion.""" import argparse import json import numpy as np from scipy.spatial.transform import Rotation from rigorous_calibration import ( inverse_transform, load_stations, rotation_angle_deg, rpy_deg, transform_points, ) COLORS = { "target": [0.10, 0.65, 1.00], "source": [1.00, 0.35, 0.05], } def cloud(o3d, points, color, voxel): item = o3d.geometry.PointCloud() item.points = o3d.utility.Vector3dVector(points) item = item.voxel_down_sample(voxel) item.paint_uniform_color(color) return item def delta_components(reference, candidate): """Components of reference^-1*candidate, plus coordinate-invariant norms.""" delta = inverse_transform(reference) @ candidate translation = np.asarray(delta[:3, 3], float) return { "translation_xyz_cm": (translation * 100.0).tolist(), "translation_norm_cm": float(np.linalg.norm(translation) * 100.0), "rotation_rpy_deg_xyz": rpy_deg(delta[:3, :3]), "rotation_angle_deg": rotation_angle_deg(delta[:3, :3]), } def body_left_rpy(x, rpy_correction_deg): correction = np.eye(4) correction[:3, :3] = Rotation.from_euler( "xyz", np.asarray(rpy_correction_deg, float), degrees=True ).as_matrix() return correction @ x def print_delta(name, reference, candidate): item = delta_components(reference, candidate) tx, ty, tz = item["translation_xyz_cm"] roll, pitch, yaw = item["rotation_rpy_deg_xyz"] print( f"{name}: B^-1*motion translation xyz = " f"[{tx:+.4f}, {ty:+.4f}, {tz:+.4f}] cm; " f"rpy xyz = [{roll:+.4f}, {pitch:+.4f}, {yaw:+.4f}] deg; " f"norm = {item['translation_norm_cm']:.4f} cm / " f"{item['rotation_angle_deg']:.6f} deg" ) return item def main(): import open3d as o3d parser = argparse.ArgumentParser(description=__doc__) parser.add_argument("--frames", required=True) parser.add_argument("--pairs", required=True) parser.add_argument("--extrinsic", required=True) parser.add_argument("--pair-index", type=int, default=0) parser.add_argument("--voxel", type=float, default=0.10) parser.add_argument( "--left-rpy-deg", nargs=3, type=float, default=[0.0, 0.0, 0.0], metavar=("ROLL", "PITCH", "YAW"), help="optional body-frame left correction applied as DeltaR_body * X", ) args = parser.parse_args() stations = load_stations(args.frames, 1.0, 60.0) with np.load(args.pairs, allow_pickle=False) as data: if len(stations) != len(data["station_times"]): raise ValueError( f"frames contain {len(stations)} stations but pair file records " f"{len(data['station_times'])}" ) if not 0 <= args.pair_index < len(data["A"]): raise IndexError( f"pair-index {args.pair_index} outside [0,{len(data['A']) - 1}]" ) a_ij = np.asarray(data["A"][args.pair_index], float) b_gicp = np.asarray(data["B"][args.pair_index], float) i, j = np.asarray(data["meta"][args.pair_index, :2], int) with open(args.extrinsic, encoding="utf-8-sig") as stream: result = json.load(stream) x = np.asarray(result["matrix_4x4"], float) b_calibrated = inverse_transform(x) @ a_ij @ x transforms = { "1 raw": np.eye(4), "2 RTK initial (X0=I)": a_ij, "3 GICP B": b_gicp, "4 calibrated X^-1 A X": b_calibrated, } correction = np.asarray(args.left_rpy_deg, float) if np.any(np.abs(correction) > 0.0): x_test = body_left_rpy(x, correction) transforms[ f"5 test body-left RPY {correction.tolist()} deg" ] = inverse_transform(x_test) @ a_ij @ x_test target = stations[i][3] source = stations[j][3] print(f"pair_index={args.pair_index}, station {i} <- {j}") print("blue = target station i; orange = source station j after selected transform") print("keys: 1 raw | 2 RTK initial | 3 GICP | 4 calibrated | 5 test correction | Q/Esc exit") print( "IMPORTANT: delta xyz/rpy are components of B^-1*(X^-1*A*X), expressed " "in station-j LiDAR coordinates; screen-left/right depends on the 3D camera view." ) baseline = print_delta("mode 4 minus mode 3", b_gicp, b_calibrated) roll, pitch, yaw = np.abs(baseline["rotation_rpy_deg_xyz"]) if max(roll, pitch) > max(0.10, 2.0 * yaw): print("diagnosis: roll/pitch components dominate yaw; do not prioritize yaw tuning for this pair.") tx, ty, tz = np.abs(baseline["translation_xyz_cm"]) if tz > max(tx, ty): print("diagnosis: the largest translation component is relative Z, not lateral XY.") body_up = np.array([0.0, 0.0, 1.0]) if np.linalg.norm(a_ij[:3, :3] @ body_up - body_up) < 1e-8: print( "observability: this A preserves the body Z axis, so body-left X.z " "translation is unobservable from this pair; use ground/external height constraints." ) if "5 test body-left RPY " + str(correction.tolist()) + " deg" in transforms: print_delta("mode 5 minus mode 3", b_gicp, list(transforms.values())[-1]) viewer = o3d.visualization.VisualizerWithKeyCallback() viewer.create_window("Rigorous LiDAR registration inspection - 3D", 1400, 900) target_cloud = cloud(o3d, target, COLORS["target"], args.voxel) source_cloud = cloud(o3d, source, COLORS["source"], args.voxel) viewer.add_geometry(target_cloud) viewer.add_geometry(source_cloud) axes = o3d.geometry.TriangleMesh.create_coordinate_frame(size=1.0) viewer.add_geometry(axes) current = np.eye(4) def select(name): def callback(vis): nonlocal current desired = transforms[name] source_cloud.transform(desired @ inverse_transform(current)) current = desired vis.update_geometry(source_cloud) if name == "3 GICP B": print(f"{name}: reference registration B; delta = 0") else: print_delta(name + " minus mode 3", b_gicp, desired) return False return callback for key, name in zip((ord("1"), ord("2"), ord("3"), ord("4"), ord("5")), transforms): viewer.register_key_callback(key, select(name)) viewer.get_render_option().background_color = np.array([0.02, 0.02, 0.02]) viewer.get_render_option().point_size = 2.0 viewer.run() viewer.destroy_window() if __name__ == "__main__": main()