Detect Low Obstacles using Tilted 2D Lidar

Use cheap 2D lidar to detect obstacles and potholes. It saves your budgets

Marshal SHI
6 min readMar 27, 2022


Image from Google Image Search


In the robotics world, we normally use 2D lidar or 3D lidar to detect the obstacles as the perception sensors. Although using the camera with the deep learning model has developed very fast in recent years and it’s able to detect different objects, lidar is more convenient and “simpler” to integrate into robotics. There are a lot of mature lidar obstacle detection algorithms in the ROS system (Robotic Operation System). Normally when using lidar, you don’t need to write anything, instead you just need to configure the YAML file and all things magically work.

When using lidars, 3D lidar is able to return the 3D data points and generate the 3D map of the world such that robots can distinguish objects, such as walls, desks, or cans. But the “shortage” of 3D lidar is that it’s too expensive. When we do our personal projects or in a startup, the budget may be limited such that we cannot afford a 3D lidar. Instead, most of us will choose the 2D lidar which is around 100USD. But 2D lidar has limited ability to recognize different objects especially when the object size is small. 2D lidar barely finds the low obstacles and some robotics are using lower installed sonar to do this kind of perception. But still, sonar has its limitations as well, for instance, it may be too sensitive to detect an object which may be just a noise.

After doing research on “how to use 2D lidar to detect low obstacles”, I found that there are two papers was doing it:

In this article, I will quickly go through how I used tilted 2D lidar on my robot and sample code to detect low obstacles by using tilted 2D lidar.


Software: Make sure the ROS installed on your robot controlling PC.


  • A 2D lidar. (I am using RPLidar)
  • Installed lidar at height 0.5m to the ground.



Marshal SHI

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