Question

我想测量房间的表面积（以平方米为单位），并希望使用2D-Lidar找出平面图。我该如何实现？

在图片中，您可以看到很多点。每个点代表相对于激光雷达位置的角度和距离。这是数据集：

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如果我绘制这些数据，它们看起来就像下面的图片。现在有什么算法可以帮助我检测拐角或墙壁。我想检测拐角或墙壁，以便可以轻松找出房间表面。 For example distance from corner to corner or distance between walls help me to find out the surface area.以后，我也许可以使用OpenCV创建平面图。我不知道应该选择点云库还是图像处理。

到目前为止，我遇到了RNSAC方法和Haris角点检测。

使用RANSAC可以检测多条线及其相交吗？如果可能的话，我可能会找到房间的一角，并可以根据该角绘制平面图。
Haris角点检测会检测到所有角点吗？

我应该采取哪种方式？有更好的解决方案吗？

Answer 1

将此答案作为“正在进行的工作” 处理。欢迎其他任何人使用，使用，开发和改进它的任何方面。

我在终端中使用 ImageMagick 只是为了提高速度，但是 OpenCV 和 scikit-image 中可以使用相同的技术。 / p>

首先，我想摆脱注释并清理数据。其他人可以选择从OP的问题中获取CSV数据：

magick lidar.png -fuzz 20% -fill black +opaque "rgb(53,255,255)" -colorspace gray -auto-level -threshold 50% clean.png

这为我们提供了clean.png中数据的清晰图像：

我的第一个直觉是尝试使用“霍夫变换” 来查找墙，即直线：

magick clean.png -colorspace RGB \( +clone -background none -fill red -stroke red -strokewidth 2 -hough-lines 9x9+30 \) -composite result.png

除了以红色绘制它们之外，您还可以像这样获取检测到的线的坐标：

magick clean.png -hough-lines 9x9+30 mvg:-

输出：

# Hough line transform: 9x9+30
viewbox 0 0 929 761
# x1,y1 x2,y2 # count angle distance
line 0,30.8401 929,47.0559  # 58 91 315        <--- THIS LINE EXPLAINED BELOW
line 178.597,0 165.314,761  # 42 1 364
line 0,553.92 929,570.136  # 182 91 838

通过澄清，上面的行看起来像这样：

line 0,30.8401 929,47.0559  # 58 91 315

表示从坐标[0,30]到[929,47]有一条红线，其中x坐标位于第一位，并且有58个点组成该线。还要注意，有两条线成91度角-这很好地暗示了它们是平行的-就像房间的墙壁一样。

很难找到右侧墙...仍在思考和工作。如果/当我们得到全部四面墙时，我们可以解析地求出该线的交点以得到房间的拐角。

关于寻找拐角，如果您绘制每个角度到中心的径向距离，您应该找到4个距离的峰值，它们应该是拐角，因为它们必须距传感器最远。因此，可能看起来像这样-请注意，我在代码中对数据进行了平滑处理以消除异常值。

#!/usr/bin/env python3

from scipy import ndimage as ndi
import matplotlib.pyplot as plt
import datetime
import numpy as np
import pandas as pd

# Load CSV
df = pd.read_csv('lidar.csv',delimiter=',')
xdata = df.values[:,0]
rdata = df.values[:,1]

# Condition distance data
smoothed = ndi.gaussian_filter(rdata,sigma=5)

plt.plot(xdata,smoothed,'b.')    # blue circle

plt.title('Lidar')
plt.xlabel('angle')
plt.ylabel('distance')
plt.grid(True)
plt.show()

对该内容的快速阅读意味着这些拐角处的激光雷达角为：

25, 130, 260, 320 degrees

请注意，我已经从您的CSV文件中删除了干扰内容，所以现在看起来像这样：

0,942
0.62,3469
1.25,3350
2.5,3410
...
...

您是否控制激光雷达传感器的位置？如果是这样，您可以考虑要求操作员始终以指向某个角的扫描开始扫描，那么您将有一个很好的参考点，可以找到数据中第一个角应出现的位置。您也可以在不同的高度进行两次扫描，以减少反射产生的随机噪声。

如何从2D点云或激光雷达扫描的数据中检测出拐角？

1 个答案: