Preserving 3D Laser Point Cloud Data - A Practical Approach
Whether in the field of map making, environmental perception or robot navigation, laser point cloud is a very important data. When working with laser point cloud data, saving and managing this data is crucial. This article will introduce an effective method to save and manage laser point cloud data, and provide the corresponding source code.
First, let's understand how a laser point cloud is represented. The laser point cloud is a collection of a large number of three-dimensional coordinate points, which represent the position information of the object surface scanned by the laser sensor. In a computer, we can represent a laser point cloud with a simple data structure, the array. Each array element contains a three-dimensional coordinate representing the X, Y, and Z coordinates of the point.
Now, let's take a look at the specific methods of saving and managing laser point cloud data. We can save laser point cloud in LAS (LASer) format, which is a widely used binary file format specially designed for storing laser point cloud data. The LAS format not only supports storing point coordinate information, but also can contain other additional information, such as reflection intensity, classification labels, etc.
Next is a piece of Python code for saving laser point cloud data in LAS format:
import laspy
def save_las(point_cloud, filename):
header = laspy