Detect Low Obstacles using Tilted 2D Lidar

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

Marshal SHI

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Background

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…

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Marshal SHI

Robots make our life easier | Robotics, Reinforcement Learning, Web, Python, Rust & Life Hacking. At MotivEdge.io