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# ----------------------------------------------------------------------------
# - Open3D: www.open3d.org -
# ----------------------------------------------------------------------------
# The MIT License (MIT)
#
# Copyright (c) 2018-2021 www.open3d.org
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
# IN THE SOFTWARE.
# ----------------------------------------------------------------------------
"""Align multiple pieces of geometry in a global space"""
import open3d as o3d
import numpy as np
def load_point_clouds(voxel_size=0.0):
pcd_data = o3d.data.DemoICPPointClouds()
pcds = []
for i in range(3):
pcd = o3d.io.read_point_cloud(pcd_data.paths[i])
pcd_down = pcd.voxel_down_sample(voxel_size=voxel_size)
pcds.append(pcd_down)
return pcds
def pairwise_registration(source, target, max_correspondence_distance_coarse,
max_correspondence_distance_fine):
print("Apply point-to-plane ICP")
icp_coarse = o3d.pipelines.registration.registration_icp(
source, target, max_correspondence_distance_coarse, np.identity(4),
o3d.pipelines.registration.TransformationEstimationPointToPlane())
icp_fine = o3d.pipelines.registration.registration_icp(
source, target, max_correspondence_distance_fine,
icp_coarse.transformation,
o3d.pipelines.registration.TransformationEstimationPointToPlane())
transformation_icp = icp_fine.transformation
information_icp = o3d.pipelines.registration.get_information_matrix_from_point_clouds(
source, target, max_correspondence_distance_fine,
icp_fine.transformation)
return transformation_icp, information_icp
def full_registration(pcds, max_correspondence_distance_coarse,
max_correspondence_distance_fine):
pose_graph = o3d.pipelines.registration.PoseGraph()
odometry = np.identity(4)
pose_graph.nodes.append(o3d.pipelines.registration.PoseGraphNode(odometry))
n_pcds = len(pcds)
for source_id in range(n_pcds):
for target_id in range(source_id + 1, n_pcds):
transformation_icp, information_icp = pairwise_registration(
pcds[source_id], pcds[target_id],
max_correspondence_distance_coarse,
max_correspondence_distance_fine)
print("Build o3d.pipelines.registration.PoseGraph")
if target_id == source_id + 1: # odometry case
odometry = np.dot(transformation_icp, odometry)
pose_graph.nodes.append(
o3d.pipelines.registration.PoseGraphNode(
np.linalg.inv(odometry)))
pose_graph.edges.append(
o3d.pipelines.registration.PoseGraphEdge(source_id,
target_id,
transformation_icp,
information_icp,
uncertain=False))
else: # loop closure case
pose_graph.edges.append(
o3d.pipelines.registration.PoseGraphEdge(source_id,
target_id,
transformation_icp,
information_icp,
uncertain=True))
return pose_graph
if __name__ == "__main__":
voxel_size = 0.02
pcds_down = load_point_clouds(voxel_size)
o3d.visualization.draw(pcds_down)
print("Full registration ...")
max_correspondence_distance_coarse = voxel_size * 15
max_correspondence_distance_fine = voxel_size * 1.5
with o3d.utility.VerbosityContextManager(
o3d.utility.VerbosityLevel.Debug) as cm:
pose_graph = full_registration(pcds_down,
max_correspondence_distance_coarse,
max_correspondence_distance_fine)
print("Optimizing PoseGraph ...")
option = o3d.pipelines.registration.GlobalOptimizationOption(
max_correspondence_distance=max_correspondence_distance_fine,
edge_prune_threshold=0.25,
reference_node=0)
with o3d.utility.VerbosityContextManager(
o3d.utility.VerbosityLevel.Debug) as cm:
o3d.pipelines.registration.global_optimization(
pose_graph,
o3d.pipelines.registration.GlobalOptimizationLevenbergMarquardt(),
o3d.pipelines.registration.GlobalOptimizationConvergenceCriteria(),
option)
print("Transform points and display")
for point_id in range(len(pcds_down)):
print(pose_graph.nodes[point_id].pose)
pcds_down[point_id].transform(pose_graph.nodes[point_id].pose)
o3d.visualization.draw(pcds_down)
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