# A Survey of Low-Cost 3D Laser Scanning Technology
## 4 Problems of a Moving 2D LiDAR
### Problem II: Real-Time Performance  
For a moving 2D LiDAR, in addition to the problem on accuracy, another problem that needs to be solved urgently is its defect in real-time performance. In Section 2 of this paper, the principle of a moving 2D LiDAR has been analyzed, that is, the 2D LiDAR collects sampling points at different positions; these sampling points are converted to a global world coordinate. Through this process, a 3D point cloud of the environment can be built. During this process, multiple frames of 2D point clouds are collected by the 2D LiDAR, and eventually they are combined into a frame of 3D point cloud, which is the result of this 3D scan. Each time a 2D LiDAR collects a frame of 2D point cloud, it takes a certain amount of time. A 3D scan of a moving 2D LiDAR requires more time, because multiple frames of 2D point clouds should be collected by 2D LiDAR during this 3D scan. When the resolution of the 3D scan of a moving 2D LiDAR is higher, the 3D point cloud is denser, the number of frames of the 2D point clouds contained is more, and the time it takes to finish this 3D scan is longer. Limited by the current level of technology, the scanning frequency of most 2D LiDARs is not high enough, and the time required to finish a 2D scan is not short enough. As a result, it takes too long for a moving 2D LiDAR to finish a 3D scan. Take the 2D LiDAR UST-10 LX produced by Hokuyo as an example. Its scanning frequency is 40 Hz [36]. If it is used to build a rotating 2D LiDAR, the time required to finish a 3D scan is a few seconds to more than ten seconds (the time needed depends on the resolution setting of the 3D point cloud). In order to shorten this time, the only way is to reduce the resolution of the 3D point cloud and make the collected 3D point cloud sparser. If the 3D point cloud is sparse enough, the time required to finish a 3D scan can be shortened within 1 second. However, this may make the collected 3D point cloud too sparse to be useful. To solve the real-time problem of a moving 2D LiDAR from the root, the sampling speed of the 2D LiDAR should be fast enough, and the time required to finish one frame of 2D point cloud should be short enough, so that the time required for a moving 2 DLiDAR to build one frame of the 3D point cloud, which contains multiple frames of 2D point clouds, can be short enough. The upgrading of the sampling speed of a commercial 2D LiDAR depends on the manufacturer. Unfortunately, in recent years, sampling speed of commercial 2D LiDARs has not been upgraded significantly. After all, for the general applications of a 2D LiDAR, its current sampling speed is sufficient. For example, a 2D LiDAR is mounted on a mobile robot horizontally, when the mobile robot moves, the 2D LiDAR can collect the 2D maps of the environment, and the accuracy of the 2D maps can be considered not affected by the movement of the mobile robot. The reason is simple, taking the movement of the mobile robot as a reference, the time required to finish a frame of 2D map is very short. At the time points when the scan of a frame of 2D map starts and ends, the position and attitude of the mobile robot are virtually unchanged. However, if a rotating 2D LiDAR is mounted on a mobile robot rather than a 2D LiDAR, the situation is different. Taking the movement of the mobile robot as a reference, the time required for a frame of 3D map is so long that the position and attitude of the mobile robot may change significantly at the time points when the scan of a frame of 3D map starts and ends. This makes the accuracy of the 3D map can be influenced by the movement of the mobile robot. This problem is caused by the lack of real-time of a rotating 2D LiDAR. The lack of real-time seriously restricts the application of a moving 2D LiDAR. For a camera, an image can be obtained at a fast speed, whether the platform is moving or there are moving objects in the environment, data can be collected accurately. For a moving 2D LiDAR, because of the lack of real-time, things are different.