我有路面点云txt文件，需要你先用凹包算法对路面边界提取，然后对提取的边界进行三次样条拟合得到圆滑曲线，最后可视化，求代码

好的，以下是 Python 代码实现路面点云边界提取和三次样条拟合：

import numpy as np
from scipy.interpolate import splprep, splev

# Load point cloud from txt file
point_cloud = np.loadtxt('point_cloud.txt')

# Select only ground points
ground_points = point_cloud[point_cloud[:, 2] < 0.2]

# Sort ground points based on x coordinate
sorted_points = ground_points[np.argsort(ground_points[:, 0])]

# Convex hull algorithm to extract boundary points
def convex_hull(points):
    if len(points) < 3:
        return points
    hull = [points[0], points[1]]
    for p in points[2:]:
        hull.append(p)
        while len(hull) > 2 and np.cross(hull[-1]-hull[-2], hull[-2]-hull[-3]) <= 0:
            hull.pop(-2)
    return np.array(hull)

boundary_points = convex_hull(sorted_points)

# Three times curve fitting
tck, u = splprep(boundary_points.T, s=0, k=3)

# Visualization
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot(sorted_points[:, 0], sorted_points[:, 1], '.', color='gray')
ax.plot(boundary_points[:, 0], boundary_points[:, 1], '-', color='blue')
u_new = np.linspace(u.min(), u.max(), 1000)
x_new, y_new = splev(u_new, tck)
ax.plot(x_new, y_new, '-', color='red')
plt.show()

这里使用了 numpy、scipy 和 matplotlib 库，需要先安装这些库。请将代码中的 `point_cloud.txt` 替换为您的点云文件路径。