采用Python编写的最近点迭代算法:
import numpy as np
from scipy.spatial import KDTree
import open3d as o3d
# 读取点云数据
def read_point_cloud(file_path):
pcd = o3d.io.read_point_cloud(file_path)
return np.asarray(pcd.points)
# 将点从3维转换为4维齐次坐标
def points_to_homogeneous(points):
return np.hstack([points, np.ones((points.shape[0], 1))])
# 将点从4维齐次坐标转换为3维
def points_from_homogeneous(points_homogeneous):
return points_homogeneous[:, :3]
# 求解最优刚体变换矩阵
def compute_rigid_transform(A, B):
assert len(A) == len(B)
N = A.shape[0] # 点数
centroid_A = np.mean(A, axis=0)
centroid_B = np.mean(B, axis=0)
AA = A - centroid_A
BB = B - centroid_B
H = AA.T @ BB
U, S, Vt = np.li